Find your next LLM, RAG & AI Agent engineering role

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to customers as they adopt Claude. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting edge implementation patterns for LLMs. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability. Responsibilities: Serve as a technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation Guide technical architecture decisions and help customers build state-of-the-art products & workflows with LLMs via API Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API Lead hands-on technical workshops and code reviews with customer engineering teams Identify common design patterns and contribute insights back to our Product and Engineering teams Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks Travel occasionally to customer sites for workshops, implementation support, and building relationships Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space You may be a good fit if you have: 8+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer or Software Engineer with a desire to work closely with customers Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale Strong programming skills with proficiency in Python and experience building production applications Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks. Ability to navigate ambiguity and execute across domains with intellectual openness , finding simple solutions to complex problems High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity Passion for advancing safe, beneficial AI systems through creative technical applications Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

11d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to customers as they adopt Claude. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting edge implementation patterns for LLMs. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability. Responsibilities: Serve as a technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation Guide technical architecture decisions and help customers build state-of-the-art products & workflows with LLMs via API Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API Lead hands-on technical workshops and code reviews with customer engineering teams Identify common design patterns and contribute insights back to our Product and Engineering teams Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks Travel occasionally to customer sites for workshops, implementation support, and building relationships Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space You may be a good fit if you have: 8+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer or Software Engineer with a desire to work closely with customers Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale Strong programming skills with proficiency in Python and experience building production applications Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks. Ability to navigate ambiguity and execute across domains with intellectual openness , finding simple solutions to complex problems High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity Passion for advancing safe, beneficial AI systems through creative technical applications Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

11d ago

Research and implement state-of-the-art techniques in fine-tuning and RAG. Requires PyTorch, Hugging Face, and strong Python skills. $175,000 - $245,000.

$175k - $245k

11d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Safeguards Labs is a new team operating at the intersection of research and engineering, chartered to investigate novel safety methods that protect Claude and the people who use it. We prototype new approaches to safe models, usage safeguards, and production safety — pressure-testing ideas through offline analysis and subsets of traffic before they graduate into production systems run by our partner Safeguards teams. Our work overlaps closely with account abuse, model behavior safeguards, and other safeguard subteams, and we serve as a research arm that can take on ambitious, ambiguous problems and turn them into deployed defenses. About the role We're hiring research engineers to define and execute the Labs research agenda. You'll scope your own projects, run experiments end-to-end, and decide when an idea is ready to hand off to a production team — or when to kill it and move on. The team is small and being built deliberately around a roughly 3:1 mix of researchers to software engineers, so each person has substantial latitude over what they work on and high leverage on the team's direction. Key responsibilities Lead and contribute to research projects investigating new methods for detecting misuse of Claude, identifying malicious organizations and accounts, strengthening model safeguards, and other safety needs. Design and run offline analyses over model usage data to surface abuse patterns, build classifiers and detection systems, and evaluate their effectiveness. Develop and iterate on prototypes that could eventually feed signals into the real-time safeguards path, partnering with engineers on tech transfer. Contribute to a broader research portfolio investigating methods for detecting abusive behavior in chat-based or agentive workflows, and for training the model to robustly refrain from dangerous responses or behaviors without over-refusing. Build evaluations and methodologies for measuring whether safeguards actually work, including in agentic settings. Write up findings clearly so they inform decisions across Trust & Safety, research, and product teams. Minimum qualifications Have a track record of independently driving research projects from ambiguous problem statements to concrete results, ideally in AI, ML, security, integrity, or a related technical field. Are comfortable scoping your own work and switching between research, engineering, and analysis as a project demands. Have working familiarity with how large language models operate — sampling, prompting, training — even if LLMs aren't your primary background. Are proficient in Python and comfortable working with large datasets. Care about the societal impacts of AI and want your work to directly reduce real-world harm. Preferred qualifications Experience building and training machine learning models, including classifiers for abuse, fraud, integrity, or security applications. Knowledge of evaluation methodologies for language models and experience designing evals. Experience with agentic environments and evaluating model behavior in them. Background in trust and safety, integrity, fraud detection, threat intelligence, or adversarial ML. Experience with red teaming, jailbreak research, or interpretability methods like steering vectors. A history of taking research prototypes and transferring them into production systems. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

12d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Safeguards Labs is a new team operating at the intersection of research and engineering, chartered to investigate novel safety methods that protect Claude and the people who use it. We prototype new approaches to safe models, usage safeguards, and production safety — pressure-testing ideas through offline analysis and subsets of traffic before they graduate into production systems run by our partner Safeguards teams. Our work overlaps closely with account abuse, model behavior safeguards, and other safeguard subteams, and we serve as a research arm that can take on ambitious, ambiguous problems and turn them into deployed defenses. About the role We're hiring research engineers to define and execute the Labs research agenda. You'll scope your own projects, run experiments end-to-end, and decide when an idea is ready to hand off to a production team — or when to kill it and move on. The team is small and being built deliberately around a roughly 3:1 mix of researchers to software engineers, so each person has substantial latitude over what they work on and high leverage on the team's direction. Key responsibilities Lead and contribute to research projects investigating new methods for detecting misuse of Claude, identifying malicious organizations and accounts, strengthening model safeguards, and other safety needs. Design and run offline analyses over model usage data to surface abuse patterns, build classifiers and detection systems, and evaluate their effectiveness. Develop and iterate on prototypes that could eventually feed signals into the real-time safeguards path, partnering with engineers on tech transfer. Contribute to a broader research portfolio investigating methods for detecting abusive behavior in chat-based or agentive workflows, and for training the model to robustly refrain from dangerous responses or behaviors without over-refusing. Build evaluations and methodologies for measuring whether safeguards actually work, including in agentic settings. Write up findings clearly so they inform decisions across Trust & Safety, research, and product teams. Minimum qualifications Have a track record of independently driving research projects from ambiguous problem statements to concrete results, ideally in AI, ML, security, integrity, or a related technical field. Are comfortable scoping your own work and switching between research, engineering, and analysis as a project demands. Have working familiarity with how large language models operate — sampling, prompting, training — even if LLMs aren't your primary background. Are proficient in Python and comfortable working with large datasets. Care about the societal impacts of AI and want your work to directly reduce real-world harm. Preferred qualifications Experience building and training machine learning models, including classifiers for abuse, fraud, integrity, or security applications. Knowledge of evaluation methodologies for language models and experience designing evals. Experience with agentic environments and evaluating model behavior in them. Background in trust and safety, integrity, fraud detection, threat intelligence, or adversarial ML. Experience with red teaming, jailbreak research, or interpretability methods like steering vectors. A history of taking research prototypes and transferring them into production systems. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

12d ago

About Mistral   At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products, and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany, and Singapore. We are creative, low-ego, and team-spirited.   Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on mistral.ai/careers.   About The Job:   Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases.   You will act as the primary technical point of contact for our most strategic customers, guiding them through the entire lifecycle—from pre-sales to post-implementation—while collaborating closely with research, product, and engineering teams to shape the future of our offerings.   As a Technical Lead, you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision.   What you will do   - Deliver as an IC the critical lines of codes of our complex projects, you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions. - Lead technical teams of Applied AI Engineers, providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries. - Lead technical discussions during pre-sales, translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders. - Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives. - Drive innovation by identifying emerging trends in AI, evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment. - Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle.   How We Work in Applied AI   - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it.   About you - You are fluent in English. - You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field. - You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, or Solutions Architect) focused on AI products or enterprise solutions. - You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation. - You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale. - You are proficient in Python, PyTorch, and modern AI frameworks (e.g., LangChain, Hugging Face). Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus. - You have strong software engineering skills, including API design, backend/full-stack development, and system architecture. - You excel in technical communication, with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers. - You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent.   Ideally, you have: - Contributed to open-source projects, particularly in the LLM or AI space. - Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption. - A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities.   Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!

13d ago

About Mistral   At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products, and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany, and Singapore. We are creative, low-ego, and team-spirited.   Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on mistral.ai/careers.   About The Job:   Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases.   You will act as the primary technical point of contact for our most strategic customers, guiding them through the entire lifecycle—from pre-sales to post-implementation—while collaborating closely with research, product, and engineering teams to shape the future of our offerings.   As a Technical Lead, you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision.   What you will do   - Deliver as an IC the critical lines of codes of our complex projects, you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions. - Lead technical teams of Applied AI Engineers, providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries. - Lead technical discussions during pre-sales, translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders. - Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives. - Drive innovation by identifying emerging trends in AI, evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment. - Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle.   How We Work in Applied AI   - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it.   About you - You are fluent in English. - You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field. - You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, or Solutions Architect) focused on AI products or enterprise solutions. - You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation. - You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale. - You are proficient in Python, PyTorch, and modern AI frameworks (e.g., LangChain, Hugging Face). Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus. - You have strong software engineering skills, including API design, backend/full-stack development, and system architecture. - You excel in technical communication, with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers. - You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent.   Ideally, you have: - Contributed to open-source projects, particularly in the LLM or AI space. - Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption. - A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities.   Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!

13d ago

About The Job   Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.   The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.   Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision.   What you will do   - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback   How We Work in Applied AI   - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it.   About you   - You are fluent in English - You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences   Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch

13d ago

About The Job   Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.   The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.   Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision.   What you will do   - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback   How We Work in Applied AI   - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it.   About you   - You are fluent in English - You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences   Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch

13d ago

About Mistral   At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.   Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.   About The Job   Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.   The Applied AI Engineer is an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products and building complex enterprises use-cases. They work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations.   In this role, you’ll manage customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalizing our research in production settings.   What you will do   - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback   About you - You are fluent in English - You hold a PhD / master in AI / data science or you’re self-made - You have 7-10+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have a deep understanding of Cloud Infrastructure and how to deploy AI based products - You have deployed or built products with large scale user based - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences   Ideally you have: - Contributed to open-source projects in particular in the space of LLM - Experience as a Forward Deployed Engineer, Staff Engineer Machine Learning Engineer, Staff Data Scientist.   Benefits   We have local offices in Paris, London, Marseille, Amsterdam, Lausanne and Singapore.   France   💰 Competitive cash salary and equity 🥕 Food : Daily lunch vouchers 🥎 Sport : Monthly contribution to a Gympass subscription  🚴 Transportation : Monthly contribution to a mobility pass 🧑‍⚕️ Health : Full health insurance for you and your family 🍼 Parental : Generous parental leave policy 🌎 Visa sponsorship   UK   💰 Competitive cash salary and equity 🚑 Insurance 🚴 Transportation: Reimburse office parking charges, or 90GBP/month for public transport 🥎 Sport: 90GBP/month reimbursement for gym membership 🥕 Meal voucher: £200 monthly allowance for its meals 💰 Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)

13d ago

About Mistral   At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.   Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.   About The Job   Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.   The Applied AI Engineer is an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products and building complex enterprises use-cases. They work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations.   In this role, you’ll manage customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalizing our research in production settings.   What you will do   - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback   About you - You are fluent in English - You hold a PhD / master in AI / data science or you’re self-made - You have 7-10+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have a deep understanding of Cloud Infrastructure and how to deploy AI based products - You have deployed or built products with large scale user based - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences   Ideally you have: - Contributed to open-source projects in particular in the space of LLM - Experience as a Forward Deployed Engineer, Staff Engineer Machine Learning Engineer, Staff Data Scientist.   Benefits   We have local offices in Paris, London, Marseille, Amsterdam, Lausanne and Singapore.   France   💰 Competitive cash salary and equity 🥕 Food : Daily lunch vouchers 🥎 Sport : Monthly contribution to a Gympass subscription  🚴 Transportation : Monthly contribution to a mobility pass 🧑‍⚕️ Health : Full health insurance for you and your family 🍼 Parental : Generous parental leave policy 🌎 Visa sponsorship   UK   💰 Competitive cash salary and equity 🚑 Insurance 🚴 Transportation: Reimburse office parking charges, or 90GBP/month for public transport 🥎 Sport: 90GBP/month reimbursement for gym membership 🥕 Meal voucher: £200 monthly allowance for its meals 💰 Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)

13d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis Work closely with product and design teams to scope, prototype, and ship features for life sciences users Partner with external biotech, pharma, and academic users to understand their workflows and turn feedback into product improvements Build and maintain the engineering infrastructure behind our biology product surface — tool scaffolding, data pipelines, eval harnesses Translate biological domain knowledge into product requirements and evaluation criteria that guide model improvement Minimum Qualifications Experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Experience working in drug discovery or development at a biotech or pharma company, or conducted fundamental research in an academic setting — with an understanding of what real scientific workflows look like and where they break down Strong software engineering skills: comfortable building production-quality Python, working in large codebases, and owning infrastructure end-to-end Hands-on experience training or fine-tuning ML models (LLMs, protein language models, or other deep learning architectures) A track record of shipping computational tools or pipelines that biologists actually use Comfortable navigating ambiguity and defining problems in a rapidly evolving research environment Able to work independently while collaborating tightly with research, product, and domain-expert teams Results-oriented with a bias toward rapid iteration and measurable impact Passionate about using AI to accelerate scientific discovery while maintaining high ethical standards Preferred Qualifications 5+ years of experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Ph.D. in computational biology, bioinformatics, bioengineering, CS, or a related quantitative field — or equivalent industry experience Experience with LLM post-training: RLHF, RL from verifiable rewards, SFT data curation, or eval-driven development Direct experience with therapeutic discovery pipelines — target identification, lead optimization, ADMET modeling, or clinical data analysis Familiarity with bioinformatics tooling and pipelines (sequence analysis, structure prediction, single-cell, variant calling, etc.) Experience building agentic systems or tool-use environments Published research in ML for biology, or open-source contributions to computational biology tools Fluency with biological databases (UniProt, PDB, Ensembl, NCBI) and the ability to reason about their schemas and failure modes The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

13d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis Work closely with product and design teams to scope, prototype, and ship features for life sciences users Partner with external biotech, pharma, and academic users to understand their workflows and turn feedback into product improvements Build and maintain the engineering infrastructure behind our biology product surface — tool scaffolding, data pipelines, eval harnesses Translate biological domain knowledge into product requirements and evaluation criteria that guide model improvement Minimum Qualifications Experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Experience working in drug discovery or development at a biotech or pharma company, or conducted fundamental research in an academic setting — with an understanding of what real scientific workflows look like and where they break down Strong software engineering skills: comfortable building production-quality Python, working in large codebases, and owning infrastructure end-to-end Hands-on experience training or fine-tuning ML models (LLMs, protein language models, or other deep learning architectures) A track record of shipping computational tools or pipelines that biologists actually use Comfortable navigating ambiguity and defining problems in a rapidly evolving research environment Able to work independently while collaborating tightly with research, product, and domain-expert teams Results-oriented with a bias toward rapid iteration and measurable impact Passionate about using AI to accelerate scientific discovery while maintaining high ethical standards Preferred Qualifications 5+ years of experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Ph.D. in computational biology, bioinformatics, bioengineering, CS, or a related quantitative field — or equivalent industry experience Experience with LLM post-training: RLHF, RL from verifiable rewards, SFT data curation, or eval-driven development Direct experience with therapeutic discovery pipelines — target identification, lead optimization, ADMET modeling, or clinical data analysis Familiarity with bioinformatics tooling and pipelines (sequence analysis, structure prediction, single-cell, variant calling, etc.) Experience building agentic systems or tool-use environments Published research in ML for biology, or open-source contributions to computational biology tools Fluency with biological databases (UniProt, PDB, Ensembl, NCBI) and the ability to reason about their schemas and failure modes The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

13d ago

Manage cloud infrastructure for AI training and inference workloads on AWS and GCP using Kubernetes, Docker, and Terraform. Remote-friendly. $145,000 - $195,000.

$145k - $195k

13d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping systems integrators, startups, and other GovTech companies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with Claude Code, the Claude API, and Claude for Enterprise Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel frequently to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: US Secret Clearance preferred for working with defense tech customers Prior work in government, government contracting, or government tech preferred 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager Experience navigating complex buying cycles involving multiple stakeholders Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiar with Python Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

13d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping systems integrators, startups, and other GovTech companies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with Claude Code, the Claude API, and Claude for Enterprise Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel frequently to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: US Secret Clearance preferred for working with defense tech customers Prior work in government, government contracting, or government tech preferred 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager Experience navigating complex buying cycles involving multiple stakeholders Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiar with Python Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

13d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping state and local government agencies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with Claude Code, the Claude API, and Claude for Enterprise Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel frequently to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have Must have prior experience working with US federal, state, and/or local agencies 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager Experience navigating complex buying cycles involving multiple stakeholders Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiar with Python Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

13d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping state and local government agencies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with Claude Code, the Claude API, and Claude for Enterprise Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel frequently to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have Must have prior experience working with US federal, state, and/or local agencies 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager Experience navigating complex buying cycles involving multiple stakeholders Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiar with Python Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

13d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. À propos d’Anthropic La mission d’Anthropic est de créer des systèmes d’IA fiables, interprétables et orientables. Nous voulons que l'IA soit sûre et bénéfique pour nos utilisateurs et pour la société dans son ensemble. Notre équipe est composée de chercheurs, d'ingénieurs, d'experts politiques et de chefs d'entreprise engagés qui travaillent ensemble pour créer des systèmes d'IA bénéfiques. À propos du poste En tant qu'architecte des solutions partenaires au sein de l'équipe d'IA appliquée d'Anthropic, vous serez architecte avant-vente chargé d'entretenir des relations techniques avec nos intégrateurs de systèmes mondiaux et régionaux (GSI/RSI) et nos partenaires cloud (AWS et GCP). Vous renforcerez nos relations avec les partenaires clés pour accélérer les revenus indirects, permettre leurs pratiques d'IA et exécuter la stratégie GTM à long terme. Responsabilités : Partenariat technique stratégique : soyez un partenaire de réflexion technique pour l'équipe des partenariats Anthropic GTM, en apportant une expertise technique pour mieux comprendre l'environnement des partenaires, en pilotant des programmes stratégiques clés et en identifiant des opportunités pour approfondir leurs compétences techniques. Vous vous intégrez aux équipes techniques de GSI et des partenaires cloud pour mettre en œuvre leurs pratiques en matière d'IA, vous aider à résoudre les problèmes, promouvoir Anthropic au sein de leurs communautés de développeurs et servir de point d'accès pour les problèmes techniques complexes. Développement conjoint de solutions : Collaborer avec des partenaires pour identifier des applications GenAI spécifiques à grande valeur industrielle, développer des solutions conjointes et codifier des architectures de référence / bonnes pratiques afin d’accélérer le temps de déploiement Assistance aux offres clients : Intervenir directement pour débloquer des transactions clients stratégiques où les partenaires sont le principal vecteur de livraison, apportant une expertise technique approfondie et des conseils en architecture de solutions. Écosystème de partenaires et événements : représentez Anthropic lors d'événements partenaires tels que les ateliers clients GSI, les sommets AWS et les conférences sectorielles. Animer ou soutenir des événements, hackathons et sessions de formation technique destinés aux développeurs partenaires, en particulier pour les communautés ayant une expertise technique pointue. Retours sur les produits : validez et recueillez des retours sur les produits et services d'Anthropic, notamment en ce qui concerne les cas d'utilisation et modèles de déploiement des partenaires, et transmettez ces commentaires aux équipes Anthropic concernées afin d'éclairer la feuille de route du produit et la stratégie des partenaires. Profil recherché : Plus de 5 ans d'expérience dans des rôles techniques orientés clients et partenaires, tels que Architecte de Solutions, Ingénieur Commercial, Ingénieur Commercial Partenaires, Responsable de Compte Technique Expérience avérée de partenariats fructueux avec des intégrateurs de systèmes mondiaux et/ou des fournisseurs de services cloud pour résoudre des problèmes techniques complexes, de la conception initiale de la solution à sa mise en œuvre chez le client Capacité exceptionnelle à établir des relations avec diverses parties prenantes et à leur communiquer des concepts techniques, notamment des cadres supérieurs, des équipes informatiques et d'ingénierie, etc. Solides compétences en présentation et communication technique avec la capacité de traduire les exigences entre parties prenantes techniques et commerciales Expérience de la conception d'architectures cloud évolutives et de l'intégration avec des systèmes d'entreprise Familiarité avec les cadres et outils LLM courants ou une formation en apprentissage automatique ou en science des données Enthousiasme à l'idée de participer à une collaboration inter-organisationnelle, de trouver des compromis et de trouver un équilibre entre des priorités concurrentes L'amour de l'enseignement, du mentorat et de la réussite des autres Passion pour la réflexion créative sur la manière d'utiliser la technologie de façon sûre et bénéfique, et qui favorise ultimement l'avancement des systèmes d'IA sûrs. About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Responsibilities: Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events: Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities.Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. You may be a good fit if you have: 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: €175.000 — €215.000 EUR Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

14d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. À propos d’Anthropic La mission d’Anthropic est de créer des systèmes d’IA fiables, interprétables et orientables. Nous voulons que l'IA soit sûre et bénéfique pour nos utilisateurs et pour la société dans son ensemble. Notre équipe est composée de chercheurs, d'ingénieurs, d'experts politiques et de chefs d'entreprise engagés qui travaillent ensemble pour créer des systèmes d'IA bénéfiques. À propos du poste En tant qu'architecte des solutions partenaires au sein de l'équipe d'IA appliquée d'Anthropic, vous serez architecte avant-vente chargé d'entretenir des relations techniques avec nos intégrateurs de systèmes mondiaux et régionaux (GSI/RSI) et nos partenaires cloud (AWS et GCP). Vous renforcerez nos relations avec les partenaires clés pour accélérer les revenus indirects, permettre leurs pratiques d'IA et exécuter la stratégie GTM à long terme. Responsabilités : Partenariat technique stratégique : soyez un partenaire de réflexion technique pour l'équipe des partenariats Anthropic GTM, en apportant une expertise technique pour mieux comprendre l'environnement des partenaires, en pilotant des programmes stratégiques clés et en identifiant des opportunités pour approfondir leurs compétences techniques. Vous vous intégrez aux équipes techniques de GSI et des partenaires cloud pour mettre en œuvre leurs pratiques en matière d'IA, vous aider à résoudre les problèmes, promouvoir Anthropic au sein de leurs communautés de développeurs et servir de point d'accès pour les problèmes techniques complexes. Développement conjoint de solutions : Collaborer avec des partenaires pour identifier des applications GenAI spécifiques à grande valeur industrielle, développer des solutions conjointes et codifier des architectures de référence / bonnes pratiques afin d’accélérer le temps de déploiement Assistance aux offres clients : Intervenir directement pour débloquer des transactions clients stratégiques où les partenaires sont le principal vecteur de livraison, apportant une expertise technique approfondie et des conseils en architecture de solutions. Écosystème de partenaires et événements : représentez Anthropic lors d'événements partenaires tels que les ateliers clients GSI, les sommets AWS et les conférences sectorielles. Animer ou soutenir des événements, hackathons et sessions de formation technique destinés aux développeurs partenaires, en particulier pour les communautés ayant une expertise technique pointue. Retours sur les produits : validez et recueillez des retours sur les produits et services d'Anthropic, notamment en ce qui concerne les cas d'utilisation et modèles de déploiement des partenaires, et transmettez ces commentaires aux équipes Anthropic concernées afin d'éclairer la feuille de route du produit et la stratégie des partenaires. Profil recherché : Plus de 5 ans d'expérience dans des rôles techniques orientés clients et partenaires, tels que Architecte de Solutions, Ingénieur Commercial, Ingénieur Commercial Partenaires, Responsable de Compte Technique Expérience avérée de partenariats fructueux avec des intégrateurs de systèmes mondiaux et/ou des fournisseurs de services cloud pour résoudre des problèmes techniques complexes, de la conception initiale de la solution à sa mise en œuvre chez le client Capacité exceptionnelle à établir des relations avec diverses parties prenantes et à leur communiquer des concepts techniques, notamment des cadres supérieurs, des équipes informatiques et d'ingénierie, etc. Solides compétences en présentation et communication technique avec la capacité de traduire les exigences entre parties prenantes techniques et commerciales Expérience de la conception d'architectures cloud évolutives et de l'intégration avec des systèmes d'entreprise Familiarité avec les cadres et outils LLM courants ou une formation en apprentissage automatique ou en science des données Enthousiasme à l'idée de participer à une collaboration inter-organisationnelle, de trouver des compromis et de trouver un équilibre entre des priorités concurrentes L'amour de l'enseignement, du mentorat et de la réussite des autres Passion pour la réflexion créative sur la manière d'utiliser la technologie de façon sûre et bénéfique, et qui favorise ultimement l'avancement des systèmes d'IA sûrs. About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Responsibilities: Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events: Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities.Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. You may be a good fit if you have: 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: €175.000 — €215.000 EUR Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

14d ago

About Mistral  At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About the team The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. Our SRE team works transversally across customer engagements, enabling value creation through Mistral tech - at scale. By joining the team you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision. About The Job You will be one of the founding engineers of the Applied AI SRE sub-team. Your mission, alongside the team, is to build and operate the framework to ensure Mistral’s solution delivery is reliable and sustainable - and applied uniformly across all our accounts, both Mistral-hosted and customer-hosted. You should already have a strong understanding of what operational excellence looks like, and you’re ready to scale your impact. You will operate in four concurrent modes: - BUILD - Design for a fleet of Mistral platforms and apps. Build proactivity to reduce reactivity. Productize reliability, author runbooks, create SLO templates, implement observability. - RUN - Operate the Tier-1 customer environments that Mistral are contracted to operate. Ensure SLO compliance, own on-call and incident response, manage drift, partner with Technical Support as L3 escalation, champion high signal post-mortems. - ENABLE - Productize how Mistral deploy, secure, and scale our Applied AI solutions. Engineer on-demand provisioning, author security baseline packages, embed security guardrails, automate everything. - SECURE - Own the security operations layer for our customer-side deployments. Lead CVE response across the fleet, ship supply-chain integrity controls (SBOM, signed images, provenance), co-page with InfoSec on security incidents, enforce secure-config baselines. This is a framework-first, fleet management role at heart. If you're excited by the difference between solving one customer's problem and structurally solving the class of problem for every customer, this is the role. How We Work in Applied AI • We care about people and outputs. • What matters is what you ship, not the time you spend on it • Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. • Always ask why. The best solutions come from deep understanding, not from copying what worked before • We say what we mean. Feedback is direct, timely, and given because we care. • No politics. Low ego, high standards. • We embrace an unstructured environment and find joy in it. About you • Fluent in English. • 5+ years in SRE, Production Engineering, or DevOps, with a record of shipping tooling. • Strong multi-tenant Kubernetes fluency, namespace segmentation, network policy, RBAC, admission control, operations at scale. • On-call discipline: incident response, blameless post-mortem culture, runbook-first mindset. • Observability stack in production: Prometheus, Grafana, OpenTelemetry, Loki, Tempo, Signoz. • Infrastructure as code: Terraform, Ansible (or close equivalents). • Proficient in Python and/or Golang for tooling and automation. • Security mindset: you treat secure-SDLC, CVE response, and supply-chain integrity as reliability properties of the shipped artifact, not as someone else's job. • Strong written communication skills: runbooks, post-mortems, and customer-facing incident comms are core deliverables of this role. • Comfortable operating with high autonomy in an ambiguous, fast-paced environment — and disciplined enough to defend the team's scope when work tries to spill in. • Solid Linux internals, networking debug, and distributed-systems fundamentals. Strong plus • Cloud or application security background (AppSec, K8s security, supply chain — SBOM, cosign, SLSA). At least one of our early hires must bring this; if it's you, flag it. • Experience operating LLM / model-serving stacks in production • Experience with multi-cloud or on-prem hybrid customer environments (AWS, GCP, Azure, sovereign clouds). • Open-source contributions, particularly in SRE, observability, or security tooling.     By applying, you agree to our Applicant Privacy Policy.

17d ago

About Mistral  At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About the team The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. Our SRE team works transversally across customer engagements, enabling value creation through Mistral tech - at scale. By joining the team you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision. About The Job You will be one of the founding engineers of the Applied AI SRE sub-team. Your mission, alongside the team, is to build and operate the framework to ensure Mistral’s solution delivery is reliable and sustainable - and applied uniformly across all our accounts, both Mistral-hosted and customer-hosted. You should already have a strong understanding of what operational excellence looks like, and you’re ready to scale your impact. You will operate in four concurrent modes: - BUILD - Design for a fleet of Mistral platforms and apps. Build proactivity to reduce reactivity. Productize reliability, author runbooks, create SLO templates, implement observability. - RUN - Operate the Tier-1 customer environments that Mistral are contracted to operate. Ensure SLO compliance, own on-call and incident response, manage drift, partner with Technical Support as L3 escalation, champion high signal post-mortems. - ENABLE - Productize how Mistral deploy, secure, and scale our Applied AI solutions. Engineer on-demand provisioning, author security baseline packages, embed security guardrails, automate everything. - SECURE - Own the security operations layer for our customer-side deployments. Lead CVE response across the fleet, ship supply-chain integrity controls (SBOM, signed images, provenance), co-page with InfoSec on security incidents, enforce secure-config baselines. This is a framework-first, fleet management role at heart. If you're excited by the difference between solving one customer's problem and structurally solving the class of problem for every customer, this is the role. How We Work in Applied AI • We care about people and outputs. • What matters is what you ship, not the time you spend on it • Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. • Always ask why. The best solutions come from deep understanding, not from copying what worked before • We say what we mean. Feedback is direct, timely, and given because we care. • No politics. Low ego, high standards. • We embrace an unstructured environment and find joy in it. About you • Fluent in English. • 5+ years in SRE, Production Engineering, or DevOps, with a record of shipping tooling. • Strong multi-tenant Kubernetes fluency, namespace segmentation, network policy, RBAC, admission control, operations at scale. • On-call discipline: incident response, blameless post-mortem culture, runbook-first mindset. • Observability stack in production: Prometheus, Grafana, OpenTelemetry, Loki, Tempo, Signoz. • Infrastructure as code: Terraform, Ansible (or close equivalents). • Proficient in Python and/or Golang for tooling and automation. • Security mindset: you treat secure-SDLC, CVE response, and supply-chain integrity as reliability properties of the shipped artifact, not as someone else's job. • Strong written communication skills: runbooks, post-mortems, and customer-facing incident comms are core deliverables of this role. • Comfortable operating with high autonomy in an ambiguous, fast-paced environment — and disciplined enough to defend the team's scope when work tries to spill in. • Solid Linux internals, networking debug, and distributed-systems fundamentals. Strong plus • Cloud or application security background (AppSec, K8s security, supply chain — SBOM, cosign, SLSA). At least one of our early hires must bring this; if it's you, flag it. • Experience operating LLM / model-serving stacks in production • Experience with multi-cloud or on-prem hybrid customer environments (AWS, GCP, Azure, sovereign clouds). • Open-source contributions, particularly in SRE, observability, or security tooling.     By applying, you agree to our Applicant Privacy Policy.

17d ago

The Enterprise ML team works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale’s proprietary research, data, and infrastructure—unlocking domain expertise through high-quality data and expert feedback. As Director of Enterprise ML, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery. This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems. What You’ll Do Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments). Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution. Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes. Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally. Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent. Stay deeply connected to the research community, understanding major trends, and helping set them. Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results. What We’re Looking For Core Qualifications 8+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains. A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.). Experience and track of recording in landing major research impacts in a fast-paced environment Experience leading or managing research teams. You’re excited to mentor, coach and develop talent. Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders. Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners Nice to Have Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $289,800 — $362,250 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

17d ago

The Enterprise ML team works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale’s proprietary research, data, and infrastructure—unlocking domain expertise through high-quality data and expert feedback. As Director of Enterprise ML, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery. This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems. What You’ll Do Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments). Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution. Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes. Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally. Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent. Stay deeply connected to the research community, understanding major trends, and helping set them. Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results. What We’re Looking For Core Qualifications 8+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains. A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.). Experience and track of recording in landing major research impacts in a fast-paced environment Experience leading or managing research teams. You’re excited to mentor, coach and develop talent. Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders. Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners Nice to Have Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $289,800 — $362,250 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

17d ago

About Mistral    At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include Vibe, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.   Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.   Role summary We are seeking strong Software Engineers with cybersecurity experience to build and productionize our cybersecurity product offering. You will turn cutting-edge prototypes into robust, scalable services that power both our offensive and defensive security capabilities. Your work will directly enable Applied to deploy at client sites while giving Science the infrastructure to train against. You'll orchestrate red-team/blue-team agent loops, build on Mistral's corporate stack, and create the connectors, worker scaling, and SDKs that transform demos into production-grade services. This is a unique opportunity to shape how AI-powered cybersecurity operates at scale.   What you will do   Cyber Harness Productionization • Build and productionize the cyber harness and service prototype, turning research into deployable solutions • Orchestrate red-team / blue-team agent loops: find vuln → patch → redeploy → re-test • Develop the context engineering that enables autonomous security workflows • Create connectors, worker scaling mechanisms, SDKs, and packaging that make demos into services Mistral Stack Integration • Build on Mistral's corporate stack: Workflows (temporal-style orchestrator) and Vibe • Work with containers/Kubernetes to deploy and scale cyber capabilities • Leverage Mistral Models to power agentic security workflows • Migrate existing prototypes onto our production infrastructure Service Engineering • Design and implement the engineering foundation that enables Applied to deploy at clients • Create the infrastructure Science can train against for continuous improvement • Ensure the cyber harness is robust, scalable, and maintainable • Collaborate with security and engineering teams to integrate cyber capabilities   About you • Strong software engineer with hands-on experience building cybersecurity products or tooling • Comfortable with agentic / LLM orchestration and context engineering • Builder mindset with a track record of shipping production-quality code • Experience with distributed systems and service architecture • Strong problem-solving abilities and attention to detail • Excellent communication skills and collaborative attitude It would be ideal if you also have: • Red-teaming, offensive-tooling, or harness-building background • Experience with orchestration internals (Temporal, Workflows, or similar) • Prior experience building a "harness for X/Y use case in cybersecurity" or similar agent system • Infrastructure knowledge: containers & Kubernetes to move fast • Experience with AI/ML systems in security contexts • Contributions to open-source security or orchestration tools

18d ago

About Mistral    At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include Vibe, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.   Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.   Role summary We are seeking strong Software Engineers with cybersecurity experience to build and productionize our cybersecurity product offering. You will turn cutting-edge prototypes into robust, scalable services that power both our offensive and defensive security capabilities. Your work will directly enable Applied to deploy at client sites while giving Science the infrastructure to train against. You'll orchestrate red-team/blue-team agent loops, build on Mistral's corporate stack, and create the connectors, worker scaling, and SDKs that transform demos into production-grade services. This is a unique opportunity to shape how AI-powered cybersecurity operates at scale.   What you will do   Cyber Harness Productionization • Build and productionize the cyber harness and service prototype, turning research into deployable solutions • Orchestrate red-team / blue-team agent loops: find vuln → patch → redeploy → re-test • Develop the context engineering that enables autonomous security workflows • Create connectors, worker scaling mechanisms, SDKs, and packaging that make demos into services Mistral Stack Integration • Build on Mistral's corporate stack: Workflows (temporal-style orchestrator) and Vibe • Work with containers/Kubernetes to deploy and scale cyber capabilities • Leverage Mistral Models to power agentic security workflows • Migrate existing prototypes onto our production infrastructure Service Engineering • Design and implement the engineering foundation that enables Applied to deploy at clients • Create the infrastructure Science can train against for continuous improvement • Ensure the cyber harness is robust, scalable, and maintainable • Collaborate with security and engineering teams to integrate cyber capabilities   About you • Strong software engineer with hands-on experience building cybersecurity products or tooling • Comfortable with agentic / LLM orchestration and context engineering • Builder mindset with a track record of shipping production-quality code • Experience with distributed systems and service architecture • Strong problem-solving abilities and attention to detail • Excellent communication skills and collaborative attitude It would be ideal if you also have: • Red-teaming, offensive-tooling, or harness-building background • Experience with orchestration internals (Temporal, Workflows, or similar) • Prior experience building a "harness for X/Y use case in cybersecurity" or similar agent system • Infrastructure knowledge: containers & Kubernetes to move fast • Experience with AI/ML systems in security contexts • Contributions to open-source security or orchestration tools

18d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Responsibilities: Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events : Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities. Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. You may be a good fit if you have: 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Fluent in Japanese and English Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

20d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Responsibilities: Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events : Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities. Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. You may be a good fit if you have: 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Fluent in Japanese and English Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

20d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: As a Manager of Startups Applied AI Architects at Anthropic, you will drive adoption of frontier AI by leading a team of technical architects to help startups build AI-native products with the Claude Developer Platform. Your team is expected to win the trust of founders and engineers by supporting their technical ambitions from early product to scale. You'll bring your own builder credibility and startup instincts to the role — setting the vision for what great technical partnership looks like in the startup segment, developing a high-performing team, and personally carrying relationships with Anthropic's most strategic early-stage accounts. This is a role for a proven technical go-to-market leader who knows how to build teams that move at startup speed, earn the trust of deeply technical buyers, and turn a scrappy early engagement into a lasting technical partnership. You'll define the playbooks for nurturing and scaling new customers, set the bar for technical excellence, and grow the people — while staying close enough to the ground to know what's actually working. You will partner with the New Business sales leader and work as one team to support your customers. Responsibilities: Lead, develop, and grow a team of Startups Applied AI Architects — setting a high bar for technical credibility, customer impact, and startup-paced execution Drive team performance through clear goal-setting, regular coaching, and a culture of continuous technical development Personally lead pre-sales engagements with high-priority startup accounts, from initial technical discovery through deployment and expansion, modeling what great looks like for your team Build and own the segment's technical playbooks: how to run technical evaluations, develop customer-specific eval frameworks, architect LLM solutions for resource-constrained early-stage teams, and win against competitive alternatives Partner with aligned Account Executives and GTM leadership to shape segment strategy and drive Claude API adoption across the startup ecosystem Ensure your team consistently surfaces insights on how startups are building with Claude — emerging use cases, deployment patterns, architectural decisions — and translate that signal into actionable feedback for Product and Engineering Drive cross-functional influence across Sales, Product, and Engineering to advance startup customer needs and shape roadmap priorities Build Anthropic's technical presence and credibility in the startup ecosystem through events, conferences, workshops, and content Stay ahead of the AI engineering landscape — context engineering, eval frameworks, agentic architectures, developer tooling — and ensure your team is operating at the frontier You may be a good fit if you: Have 8+ years of experience in technical customer-facing roles (Solutions Architect, Sales Engineer, Forward Deployed Engineer, or similar), with 5+ years leading and managing pre-sales or technical go-to-market teams Have a strong track record of building and developing high-performing SA teams — you know how to hire well, coach effectively, and create an environment where technical talent grows and does their best work Have deep experience working with startups or high-growth technology companies — you understand the velocity, constraints, and culture of early-stage companies and know how technical decisions get made at each stage of the journey Bring genuine builder credibility: you've built and deployed LLM-powered applications, you speak the language of founders and founding engineers, and you can earn the trust of deeply technical audiences without relying on a title Have hands-on expertise with context engineering, LLM evaluation frameworks, and modern AI architectures, and can guide both your team and customers through the decisions that separate a prototype from a production-grade system Are comfortable with Python and fluent in the LLM frameworks, tools, and integration patterns common in startup engineering stacks Are energized by building in ambiguous environments — you're excited to define the playbook, not just run it, and you thrive in fast-moving contexts where the technology and the customer segment are both evolving rapidly Have a genuine passion for making powerful technology safe and societally beneficial Strong candidates may have: Experience as a technical founder or in a founder-led sales motion, giving you firsthand understanding of what technical buyers in the startup world are actually evaluating A track record of winning competitive technical evaluations against other LLM providers Experience building foundational team infrastructure from the ground up: hiring frameworks, onboarding programs, technical playbooks, and coaching systems in a high-growth environment Deep familiarity with how developer infrastructure procurement evolves from seed through Series B and beyond, and how to adapt your team's approach accordingly A visible technical presence in the startup or AI engineering community through conference talks, written content, or open-source contributions The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $315,000 — $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

20d ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: As a Manager of Startups Applied AI Architects at Anthropic, you will drive adoption of frontier AI by leading a team of technical architects to help startups build AI-native products with the Claude Developer Platform. Your team is expected to win the trust of founders and engineers by supporting their technical ambitions from early product to scale. You'll bring your own builder credibility and startup instincts to the role — setting the vision for what great technical partnership looks like in the startup segment, developing a high-performing team, and personally carrying relationships with Anthropic's most strategic early-stage accounts. This is a role for a proven technical go-to-market leader who knows how to build teams that move at startup speed, earn the trust of deeply technical buyers, and turn a scrappy early engagement into a lasting technical partnership. You'll define the playbooks for nurturing and scaling new customers, set the bar for technical excellence, and grow the people — while staying close enough to the ground to know what's actually working. You will partner with the New Business sales leader and work as one team to support your customers. Responsibilities: Lead, develop, and grow a team of Startups Applied AI Architects — setting a high bar for technical credibility, customer impact, and startup-paced execution Drive team performance through clear goal-setting, regular coaching, and a culture of continuous technical development Personally lead pre-sales engagements with high-priority startup accounts, from initial technical discovery through deployment and expansion, modeling what great looks like for your team Build and own the segment's technical playbooks: how to run technical evaluations, develop customer-specific eval frameworks, architect LLM solutions for resource-constrained early-stage teams, and win against competitive alternatives Partner with aligned Account Executives and GTM leadership to shape segment strategy and drive Claude API adoption across the startup ecosystem Ensure your team consistently surfaces insights on how startups are building with Claude — emerging use cases, deployment patterns, architectural decisions — and translate that signal into actionable feedback for Product and Engineering Drive cross-functional influence across Sales, Product, and Engineering to advance startup customer needs and shape roadmap priorities Build Anthropic's technical presence and credibility in the startup ecosystem through events, conferences, workshops, and content Stay ahead of the AI engineering landscape — context engineering, eval frameworks, agentic architectures, developer tooling — and ensure your team is operating at the frontier You may be a good fit if you: Have 8+ years of experience in technical customer-facing roles (Solutions Architect, Sales Engineer, Forward Deployed Engineer, or similar), with 5+ years leading and managing pre-sales or technical go-to-market teams Have a strong track record of building and developing high-performing SA teams — you know how to hire well, coach effectively, and create an environment where technical talent grows and does their best work Have deep experience working with startups or high-growth technology companies — you understand the velocity, constraints, and culture of early-stage companies and know how technical decisions get made at each stage of the journey Bring genuine builder credibility: you've built and deployed LLM-powered applications, you speak the language of founders and founding engineers, and you can earn the trust of deeply technical audiences without relying on a title Have hands-on expertise with context engineering, LLM evaluation frameworks, and modern AI architectures, and can guide both your team and customers through the decisions that separate a prototype from a production-grade system Are comfortable with Python and fluent in the LLM frameworks, tools, and integration patterns common in startup engineering stacks Are energized by building in ambiguous environments — you're excited to define the playbook, not just run it, and you thrive in fast-moving contexts where the technology and the customer segment are both evolving rapidly Have a genuine passion for making powerful technology safe and societally beneficial Strong candidates may have: Experience as a technical founder or in a founder-led sales motion, giving you firsthand understanding of what technical buyers in the startup world are actually evaluating A track record of winning competitive technical evaluations against other LLM providers Experience building foundational team infrastructure from the ground up: hiring frameworks, onboarding programs, technical playbooks, and coaching systems in a high-growth environment Deep familiarity with how developer infrastructure procurement evolves from seed through Series B and beyond, and how to adapt your team's approach accordingly A visible technical presence in the startup or AI engineering community through conference talks, written content, or open-source contributions The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $315,000 — $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

20d ago

Role summary Scale’s Operations Planning Team sits at the intersection of Engagement Management (EM), GenAI Delivery, GTM, and Growth Ops. The Planning TPM reduces friction between customer requirements and delivery by centralizing planning, standardizing reporting, and driving consistent process execution across accounts. As a TPM on Planning you will own program-level planning and systems workstreams that translate demand into reliable production plans, validate staffing, and ensure opportunities move through ingest accurately. This role combines program management, operational rigor, analytics literacy, and strong stakeholder management, with the goal of making account planning predictable, auditable and scalable. This is a role designed to build deep account knowledge: each Planning TPM will ultimately be assigned to support 1–2 priority accounts to develop the context and relationships required to drive lasting operational improvements and more accurate planning and forecasting. What you’ll own (key responsibilities) Demand Forecasting Ensure project-level customer demand is captured accurately, consistently and at the right level of granularity. Own day-to-day monitoring and execution of Production Plan and Opportunity Forecast; act quickly on demand changes. Partner with Supply Ops to review the Production Plan weekly (PP, TCD, historical productive hours) and drive forecasting accuracy and adjustments. Surface forecast risks and coordinate tactical interventions through the Ops Planning leads. Staffing & Resource Planning Create/validate staffing requests and communicate staffing changes to Delivery teams, STOs and EMs. Monitor account-level FTE budgets and employee spend; contribute to cost/benefit analysis of staffing vs. revenue. Stress-test staffing scenarios to provide early warnings on headcount risks and to inform hiring / reallocation decisions. Validate staffing tracking accuracy weekly; identify and correct discrepancies in project-level staffing data. Opportunity Forecast & Ingest Ensure all revenue-generating opportunities are correctly logged in Opportunity Ingest (Linear) and that scoping is consistent. Act as the owner for opportunities as they move through the ingest workflow — expedite translation of demand signals into the forecast (Airtable / PP / OF). Run weekly checks to confirm Opportunity Forecast accuracy, and coordinate tactical scoping fixes when needed. Account Intelligence & Systems Enablement Actively participate in core account meetings (ops, finance, GTM, delivery) as the Ops demand operational lead. Design, build and maintain scalable planning tools and account-level reporting artifacts (ramp planning sheets, account dashboards, account playbooks). Standardize and centralize information flow across customer ops pillars (demand forecasting, staffing, opportunity ingest). Drive systems enablement, process documentation (SOPs), and handoffs that reduce manual work and increase reliability. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco and New York is: $151,200 — $189,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models. The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI. You will: Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery. Design and implement scheduling primitives to optimize the lifecycle of training jobs. Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability. Work closely with Finance and Procurement teams to drive our capacity planning process. Participate in our team’s on call process to ensure the availability of our services. Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment. Ideally you'd have: 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes). Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++) Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling. Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling. Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware. Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform). Proven ability to solve complex problems and work independently in fast-moving environments. Nice to haves: Experience with distributed training techniques such as DeepSpeed, FSDP, etc. Experience with the NVIDIA software and hardware stack (CUDA, NCCL) Experience with PyTorch Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

Role summary Scale’s Operations Planning Team sits at the intersection of Engagement Management (EM), GenAI Delivery, GTM, and Growth Ops. The Planning TPM reduces friction between customer requirements and delivery by centralizing planning, standardizing reporting, and driving consistent process execution across accounts. As a TPM on Planning you will own program-level planning and systems workstreams that translate demand into reliable production plans, validate staffing, and ensure opportunities move through ingest accurately. This role combines program management, operational rigor, analytics literacy, and strong stakeholder management, with the goal of making account planning predictable, auditable and scalable. This is a role designed to build deep account knowledge: each Planning TPM will ultimately be assigned to support 1–2 priority accounts to develop the context and relationships required to drive lasting operational improvements and more accurate planning and forecasting. What you’ll own (key responsibilities) Demand Forecasting Ensure project-level customer demand is captured accurately, consistently and at the right level of granularity. Own day-to-day monitoring and execution of Production Plan and Opportunity Forecast; act quickly on demand changes. Partner with Supply Ops to review the Production Plan weekly (PP, TCD, historical productive hours) and drive forecasting accuracy and adjustments. Surface forecast risks and coordinate tactical interventions through the Ops Planning leads. Staffing & Resource Planning Create/validate staffing requests and communicate staffing changes to Delivery teams, STOs and EMs. Monitor account-level FTE budgets and employee spend; contribute to cost/benefit analysis of staffing vs. revenue. Stress-test staffing scenarios to provide early warnings on headcount risks and to inform hiring / reallocation decisions. Validate staffing tracking accuracy weekly; identify and correct discrepancies in project-level staffing data. Opportunity Forecast & Ingest Ensure all revenue-generating opportunities are correctly logged in Opportunity Ingest (Linear) and that scoping is consistent. Act as the owner for opportunities as they move through the ingest workflow — expedite translation of demand signals into the forecast (Airtable / PP / OF). Run weekly checks to confirm Opportunity Forecast accuracy, and coordinate tactical scoping fixes when needed. Account Intelligence & Systems Enablement Actively participate in core account meetings (ops, finance, GTM, delivery) as the Ops demand operational lead. Design, build and maintain scalable planning tools and account-level reporting artifacts (ramp planning sheets, account dashboards, account playbooks). Standardize and centralize information flow across customer ops pillars (demand forecasting, staffing, opportunity ingest). Drive systems enablement, process documentation (SOPs), and handoffs that reduce manual work and increase reliability. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco and New York is: $151,200 — $189,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models. The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI. You will: Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery. Design and implement scheduling primitives to optimize the lifecycle of training jobs. Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability. Work closely with Finance and Procurement teams to drive our capacity planning process. Participate in our team’s on call process to ensure the availability of our services. Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment. Ideally you'd have: 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes). Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++) Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling. Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling. Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware. Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform). Proven ability to solve complex problems and work independently in fast-moving environments. Nice to haves: Experience with distributed training techniques such as DeepSpeed, FSDP, etc. Experience with the NVIDIA software and hardware stack (CUDA, NCCL) Experience with PyTorch Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generative AI. At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development. Strong written and verbal communication skills to operate in a cross-functional team. Nice to have: Experience with mechanistic interpretability, probing, or other techniques for understanding model internals. Familiarity with red-teaming or adversarial evaluation of post-trained models. Experience studying failure modes introduced or masked by post-training, such as reward hacking, sycophancy, or alignment faking. Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in machine learning, particularly in generative AI. At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development. Strong written and verbal communication skills to operate in a cross-functional team. Nice to have: Experience in crafting evaluations and benchmarks, or a background in data science roles related to LLM technologies. Experience with red-teaming or adversarial testing of AI systems. Familiarity with AI safety policy frameworks (e.g., NIST AI RMF, EU AI Act, Korea AI Basic Act). Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

Scale Labs, Research Scientist — AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable designing control and monitoring experiments for AI systems, building prototype systems, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in machine learning, particularly in generative AI. At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development. Strong written and verbal communication skills to operate in a cross-functional team. Nice to have: Experience with runtime monitoring, anomaly detection, or observability for ML systems. Familiarity with AI control or alignment research (e.g., scalable oversight, interpretability, debate). Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generative AI. At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development. Strong written and verbal communication skills to operate in a cross-functional team. Nice to have: Hands-on experience with agent evaluation frameworks such as SWE-bench, WebArena, OSWorld, Inspect, or similar tools. Experience with red-teaming, prompt injection, or adversarial testing of AI systems. Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

Scale AI builds the data infrastructure that powers the world’s most advanced AI. We are the trusted data partner behind frontier model makers and enterprise AI teams — providing the high-quality training data, evaluation frameworks, and human-feedback systems that make models smarter, safer, and more capable. Scale operates as a two-sided marketplace. On the demand side , our customers — leading AI labs and enterprises — need precisely labeled, expert-curated data to train and evaluate their models. On the supply side , we work with a global network of 500,000+ skilled contributors across 100+ countries who perform the complex annotation, evaluation, and data-generation tasks that fuel AI progress. Product Managers at Scale sit at the intersection of these two sides, shaping the systems, tooling, and experiences that make this marketplace work at unprecedented quality and scale. We are hiring Product Managers across multiple teams within our GenAI organization. These roles span both demand-side products (the tools and platforms our customers interact with) and supply-side products (the systems that power our contributor ecosystem). Each role offers the opportunity to work on high-impact, technically complex problems at the frontier of AI — with dedicated engineering, design, and data science teams. About the Role Scale’s GenAI platform is how the world’s leading AI companies — from frontier model labs to Fortune 500 enterprises — create the training data that makes their models best-in-class. As a PM here, you are building the systems that directly shape AI model quality. These roles are deeply cross-functional. You will work with dedicated engineering, design, and data science teams, as well as operations, finance, growth, and customer-facing stakeholders. The problems are technically complex, the pace is fast, and the impact is measurable. Whether you are on the demand side (shaping the products customers use to create and evaluate training data) or the supply side (building the systems that power our global contributor marketplace), you will own your product area end-to-end — from strategy to execution to instrumentation. Scale is a growth-stage company with the resources of a well-funded leader and the urgency of a startup. PMs here operate with significant autonomy, ship frequently, and are expected to be deeply analytical and hands-on. Example Product Management Openings: Task UX (Demand Side) — Own the end-to-end tasking product. You will define how tasks are designed, how contributors interact with multi-turn chat interfaces, and how in-task quality is measured and enforced across diverse conversational modalities. This is a critical surface area for training the next generation of models. Multi-Dimensional Quality (Demand Side) — Own Scale’s MDQ measurement framework, the CoPilot assisted-annotation experience, and our data pipeline connectivity layer. You will drive the core data quality infrastructure that customers depend on — defining how quality is decomposed, measured, and surfaced, while building AI-assisted tooling that helps contributors produce higher-quality outputs faster. Pay & Incentives (Supply Side) — This PM owns the payment and incentive systems that serve Scale’s global contributor base. You will ensure 500,000+ contributors across 100+ countries are paid accurately and on time, set pay rates methodically by skill and geography, and design incentive structures that balance cost efficiency, data quality, and contributor satisfaction. This role sits at the intersection of marketplace economics, global payments operations, and contributor experience. You Will Set the product strategy and roadmap for your area, grounded in customer needs, data analysis, and business impact Develop and execute a data-driven product roadmap through close collaboration with senior leadership, engineering, operations, data science, analytics, and design Translate customer and internal-user needs into clear, well-defined functional and technical requirements backed by data analysis and deep understanding of your users Guide and interface closely with engineering and data teams to define scope, review and refine technical capabilities, prioritize projects for release, and identify new opportunities Build long-term instrumentation, monitoring, and evaluation capabilities for product performance tracking and insight generation Establish business cases and projected return on investment to identify and prioritize opportunities Partner with finance and business leaders to manage impact on the profitability and growth of the overall business Communicate product vision, strategy, and progress to executive stakeholders and cross-functional partners Ideally, You’d Have 4–10 years of experience in Product Management in the tech industry, with scope appropriate to level (L4: 4–6 yrs, L5: 6–8 yrs, L6: 8–10+ yrs) Strong business acumen and analytical rigor, with demonstrated success driving products in ambiguous, high-growth environments Experience translating complex technical systems into clear product strategies — comfort engaging deeply with engineering and data science teams Excellent communication and stakeholder management skills, capable of influencing across technical and non-technical audiences Experience building products from the ground up and iterating through the scaling journey of a business Bachelor’s or advanced degree in a quantitative, engineering, or related discipline Nice to Have: Experience in AI/ML, data infrastructure, or marketplace businesses Strong understanding of the AI landscape — model training workflows, data labeling, evaluation, and deployment Experience with global payment systems, contributor/gig-economy platforms, or trust & safety domains Experience working at high-growth startups or scaling consumer/enterprise platforms Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $205,600 — $257,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generative AI. At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development. Strong written and verbal communication skills to operate in a cross-functional team. Nice to have: Experience with mechanistic interpretability, probing, or other techniques for understanding model internals. Familiarity with red-teaming or adversarial evaluation of post-trained models. Experience studying failure modes introduced or masked by post-training, such as reward hacking, sycophancy, or alignment faking. Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

20d ago