AI Engineering Jobs in San Francisco

Anthropic

Anthropic is dedicated to building AI systems that are safe, reliable, and steerable, aiming to benefit both users and society. This role is central to advancing Reinforcement Learning (RL), the core technology enabling Claude's reasoning, coding, and autonomous capabilities. The RL Scaling team focuses on how RL performance, stability, and learning efficiency evolve with increasing model size, episode length, and compute power. You will be instrumental in developing and scaling next-generation RL algorithms and architectures, from initial research to large-scale deployment, while deeply understanding and addressing the challenges that arise at scale. This position bridges research and engineering, requiring you to build the systems that accelerate iteration and experimentation, and to tackle complex, unsolved problems in Anthropic's largest RL runs.

$500k - $850k

Latent is seeking a Machine Learning Engineer, Research, to lead the design and development of innovative modeling approaches that push the boundaries of clinical intelligence. This role involves driving research from initial problem definition to validated outcomes, influencing how models learn from longitudinal patient data. We are looking for senior and staff-level engineers adept at managing critical research challenges from inception to completion, with a focus on problems that directly impact patient well-being.

$225k - $300k

Salesforce is seeking a highly accomplished technologist to join their Forward Deployed Engineering Team as an Expert Agent Builder. This role is at the pinnacle of AI technical expertise, focusing on architecting, designing, and building complex agentic systems to solve challenging customer problems. The successful candidate will translate ambiguous customer needs into concrete, executable AI solutions, driving transformative AI solutions by tackling the technical frontier of intelligent automation. This involves building first-of-their-kind, best-in-class experiences for major brands, including headless agent automations, dynamic AI-driven custom user interfaces, and complex multi-agent solutions. The role demands unparalleled software development mastery, deep software architecture skills, and a relentless focus on implementing engineering best practices to deliver maximum tangible value in dynamic, real-world enterprise environments.

$158k - $288k

Anthropic

Reinforcement learning is crucial for training AI models to reason, write code, and act autonomously. At scale, this process involves a demanding distributed system where training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. This system must continuously exchange data and maintain progress despite hardware failures, shifting loads, and evolving research. The efficiency of this system directly impacts learning outcomes and the speed of research iteration. As a Research Engineer on the Distributed Systems team within RL Engineering, you will focus on the most critical bottlenecks within this system. This could involve areas like scheduling, data movement, sandboxed environment execution, storage, networking, fault tolerance, autoscaling, or observability. The role seeks generalist engineers capable of reasoning from first principles across different system layers and prioritizing impactful problems over familiar ones. The ideal candidate will have experience building and operating large distributed systems, a commitment to detail, and a desire to apply their expertise to a complex, heterogeneous, and rapidly changing workload.

$500k - $850k

Latent is seeking a Machine Learning Engineer to join their team and build systems that run in real clinical workflows. This role involves owning the design, development, and operation of production-grade ML systems from ambiguous problem definition through to reliable production deployment. The ideal candidate will drive systems end-to-end, setting technical direction and taking ownership of critical systems that directly impact real patient outcomes. This is an opportunity to work on mission-critical problems at the intersection of AI and healthcare within a fast-growing, early-stage company backed by top-tier investors.

$225k - $300k

Salesforce is seeking a Senior AI Engineer to join the Agentforce Operations team, a high-velocity 'startup-within-Salesforce' focused on revolutionizing the public sector supply chain with an AI-powered platform. This role offers the unique opportunity to build a '0 to 1' product in a rapidly growing vertical, working alongside a founding team with deep startup roots but backed by the global scale of Salesforce. You will be instrumental in shaping both the product and the engineering team, partnering with product leaders and sector experts to deliver trusted AI systems for mission-critical public-sector workflows. The role involves building AI features tailored to public-sector customers, designing systems with security, compliance, reliability, and operational constraints at their core, and operating with wide autonomy to raise the bar for technical quality and mentorship.

$149k - $224k

Anthropic

The Account Abuse team is responsible for ensuring Anthropic's computing capacity is allocated fairly by minimizing resources for bad actors and preventing their return. As a software engineer on this team, you will build the machine learning systems that detect and stop abuse at scale. The ideal candidate can anticipate opponent strategies and responses to countermeasures. This role involves full-stack machine learning engineering across model training, productionization, and evaluation, with opportunities to leverage Claude to accelerate model development and maintenance. The focus is on classical ML applied to structured and behavioral data, emphasizing robust production systems, precise measurement, and safe rollout strategies, as false positives can lead to legitimate customer lockout.

$320k - $485k

About HUD HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs. About the role We’re looking for a Research Engineer for our Robotics team to develop the datasets and evals that make robotics data useful for training and evaluating embodied AI systems. You’ll translate open-ended research needs into data specifications, build methods to validate data, and run experiments to understand which data and structures improve model performance. Responsibilities - Research the data needs of robot learning and physical AI systems, and turn them into concrete dataset and evaluation specifications - Define data schemas, annotations, ground truth, and quality standards across robotics data types - Design collection and review protocols that external data providers can execute reliably - Build tools and validation workflows to audit datasets, identify quality issues, and give providers actionable feedback - Run experiments and analyze model behavior to understand how data quality, coverage, and structure affect performance - Work with HUD’s research and engineering teams, and when needed with data vendors and buyers, to improve robotics data offerings Experience You may be a good fit if you have: - Experience in robotics, robot learning, embodied AI, or closely related multimodal research - Proficiency in Python and experience building data processing, analysis, or evaluation tools - Experience turning research questions into dataset specifications, experiments, and measurable quality criteria - Strong understanding of what makes robotics data useful for training or evaluation—and where it can be misleading - Attention to detail and the ability to spot subtle errors, coverage gaps, and failure modes in complex data - Experience building research tools or pipelines without a fully prescribed roadmap Strong candidates may also have: - Worked with robot trajectories, demonstrations, video, sensor data, simulation, or other multimodal robotics datasets - Experience with imitation learning, reinforcement learning, or vision-language-action models - Worked in unstructured problem spaces and take ownership from early research through production deployment - Early-stage startup experience and strong communication skills for collaboration across teams and time zones We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria. Team & company details - Team Size: ~25 people currently, mostly full-time in-person, but some remote. - Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. - Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand. Logistics - Employment: Full-time. - Location: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones. - Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore. - Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial. What we offer - Competitive compensation - 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees) - Lunch and dinner for in-office employees - Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays - Other perks including an Equinox membership, 401k, and commuter benefits (US employees) and a health/wellness stipend (Singapore employees) - Unlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is. - Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place - Annual travel budget to visit either office Compensation Actual offers are adjusted for experience and location, but our base salary bands are - San Francisco (and other major US cities): $135,000 - $230,000 - Singapore: $100,000 - $175,000 - Rest of world: $100,000 - $175,000 Due to high volume, we may not actively respond to every application, but feel free to contact us at [email protected] or elsewhere if we missed your application!

$100k - $230k

FAR.AI is a non-profit AI research institute dedicated to ensuring advanced AI is safe and beneficial. The Applied White-Box Methods team focuses on developing, evaluating, and demonstrating techniques that utilize model internals to enhance AI system safety. This involves exploring applications like white-box control, evaluation awareness, and shaping training dynamics for improved alignment. The team bridges the gap between exploratory research and practical deployment by rigorously testing white-box methods on real-world tasks, such as long-context agentic coding, and using feedback to refine these methods for frontier-scale deployment. The scope encompasses any method using model internals for understanding, predicting, or intervening in model behavior, including activation explainers, steering, patching, influence functions, and singular learning theory. These methods are evaluated against strong black-box baselines to ensure their practical value.

$150k - $250k

Cerebras

The Core ML team is seeking an engineer to map novel algorithms for efficient large-scale AI training and inference to the Cerebras architecture. This role involves determining when these algorithms outperform competing approaches and how their advantages scale with models, workloads, and hardware. You will combine analytical performance modeling, empirical benchmarking, and hands-on prototyping to characterize the efficiency frontiers of emerging ML algorithms. Your work will span kernel-level and end-to-end performance, influencing research directions, implementation on current systems, and future hardware/software capabilities.

Salary not listed

Handshake is seeking a Member of Technical Staff to join their AI Engineering team. This role is crucial for building and improving the data systems that power frontier model training. You will be responsible for enhancing how Handshake generates, processes, and prepares complex and sensitive data, including creating high-quality synthetic data and anonymizing acquired data while preserving its value. You will collaborate with researchers, domain experts, legal teams, and customers to transform data-related challenges into experiments, pipelines, and products, influencing the company's technical direction and culture.

$200k - $350k

Anthropic

Anthropic is building reliable, interpretable, and steerable AI systems to be safe and beneficial for users and society. The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences across AWS, GCP, Azure, and other cloud providers. This involves owning the end-to-end product on each platform, from API integration and intelligent request routing to inference execution, capacity management, and operations. Engineers on this team are highly leveraged, driving multiple revenue streams while optimizing compute resources. The role requires product-minded backend engineers who can navigate platform differences, design cross-provider services and abstractions, and make architectural decisions for reliability and cost-effectiveness at massive scale. The work directly contributes to increasing service scale, accelerating the launch of new models and features, and ensuring LLMs meet rigorous safety, performance, and security standards.

$320k - $485k

Cerebras

The Core ML team is seeking an engineer to bridge the gap between novel machine learning research and efficient execution on Cerebras systems. You will work across ML frameworks, compilers, runtimes, and low-level kernels to implement new algorithmic capabilities, diagnose performance bottlenecks, and transform research prototypes into robust, high-performance demonstrations. Depending on your background, your work may emphasize runtime capabilities such as token orchestration, scheduling, communication, and distributed execution; low-level kernel development for novel ML operations; or a combination of both. This role is crucial for advancing the capabilities of Cerebras' unique AI chip architecture.

Salary not listed

Anthropic

The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences of developers and enterprise companies across major cloud platforms like AWS, GCP, and Azure. Within this team, the model & inference launch team focuses on the validation pipeline for inference servers and load balancers. This critical infrastructure work ensures that every inference change, including new model launches and performance improvements, is deployed with correctness, performance, and reliability. The goal is to make validation fast, cost-effective, and trustworthy, directly impacting how quickly advanced models and features reach users on all cloud platforms and how efficiently compute resources are utilized.

$320k - $485k

Anthropic

The Computer Use team at Anthropic focuses on enabling Claude to interact with computer interfaces and builds the necessary agent harness and end-user products. This team is integral to the research organization, bridging the gap between product development and model capabilities. As a Product Engineer, you will be responsible for the complete lifecycle of our computer-use and browser-control product surfaces, working across the full stack from user interface to agent runtime and backend services. You will collaborate directly with researchers, ensuring a close connection to the model and user experience. This role demands adaptability, a high tolerance for ambiguity, and the ability to prioritize effectively in a fast-paced environment where priorities frequently shift.

$300k - $320k

Anthropic

Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. Decisions in production training depend on knowing how the model is really behaving. This role's mission is to have the best observability into production post-training runs at Anthropic, providing the clearest, most trusted view of model quality during training. You will shape what gets measured, keep the signal trustworthy and timely, and investigate surprising results to inform post-training and release decisions.

$500k - $850k

Salient

Salient is seeking a Telephony Infrastructure Engineer to take ownership of the voice platform that powers our AI agents. This role involves managing the SIP edge, Asterisk, voice audio and dialing layers, and call servers. You will collaborate with AI agent engineers, telephony specialists, customer success teams, and carriers to ensure the platform's reliability, safety, and scalability for future growth. This is a hands-on position where you will complete ongoing projects, enhance platform stability, and prepare it to handle significantly increased call volumes. Additionally, you will design and implement customer telephony integrations, working towards making these processes more self-serve.

$200k - $300k

Faire is seeking a Senior Applied AI/ML Scientist to join the Listing Quality team. This role will focus on developing and implementing algorithmic solutions to revolutionize the wholesale industry by improving product catalog content. You will be responsible for the modeling and measurement of product images, titles, descriptions, and attributes, leveraging multi-modal deep learning and LLMs to enhance product discoverability and sales. This is a high-impact position where you will drive projects end-to-end, from problem framing to production and measurement, working with unstructured data to solve challenging marketplace problems.

$211k - $291k

DevRev is building the first agentic platform that unifies customer support and software development on a shared knowledge graph. The Tech Alliances team drives deep technical partnerships with major AI and cloud platforms. We are hiring a Tech Alliance Architect to be the technical lead for these partnerships. This role involves identifying joint value, building solutions and reference architectures, and evangelizing this value to both business and technical audiences.

Salary not listed

Salesforce is seeking an early-career, highly driven Value Acceleration Engineer to join their Agentforce for Supply Chain team. In this forward-deployed role, you will work directly with enterprise customers and Customer Success teams to implement AI-powered solutions for supply chain management. Your primary goal will be to compress the customer's time-to-value by designing and building agentic workflows and getting critical business processes live in production within an intensive 90-day window. This role is structured as a rotational "Field Residency," where you will spend the initial 6-12 months mastering production edge cases and customer complexities before transitioning into a core product and engineering pod, bringing valuable frontline insights to shape the future platform.

$117k - $224k

Faire is seeking a Senior Applied AI/ML Scientist to join their Marketplace Quality team. In this role, you will be responsible for developing and implementing algorithmic solutions to ensure the trustworthiness of Faire's marketplace for brands and retailers. This involves matching Faire's catalog against external data, detecting pricing and policy violations, and optimizing actions based on finite resources. You will work with structured and unstructured data, employing techniques like entity resolution, information extraction, multi-modal LLMs, and constrained optimization. The position requires driving projects from conception to production and measurement, in close collaboration with product, engineering, and operations teams.

$211k - $291k

Chai Discovery

Chai Discovery is building the computer-aided design suite for molecules, with major pharmaceutical companies already using their platform to accelerate drug discovery. They are at the forefront of reinventing life sciences through AI, developing frontier models that understand biochemical structure and interaction. This role is an opportunity to push the boundaries of AI drug design alongside a skilled and dedicated team.

Salary not listed

Eventual is building data curation for Physical AI, processing petabyte-scale video and sensor data to extract signals about how hands and objects interact, temporal events, and clip reliability for training frontier models. We are a small, well-backed team from leading tech companies, aiming to revolutionize how Physical AI models are trained by providing reliable, curated datasets derived from vast amounts of video footage. This role is based in our SF Mission District office, with a 4-day work week. As Technical Lead, Multimodal Research, you will drive the technical vision for Eventual's understanding of video data. You will own the strategy for selecting, prototyping, and deploying models and representations at scale, ensuring they meet rigorous evaluation standards and cost-efficiency targets. This is a senior individual contributor role focused on setting research direction and making key architectural decisions, while remaining hands-on with research and experimentation.

$150k - $300k

Mercor is a leading AI data company that organizes human intelligence to power the AI economy. We build the layer between human expertise and frontier models, enabling millions of domain experts to train AI models at scale. As a Tech Lead for the Applied AI Backend Systems, you will own critical services within our platform, focusing on designing data models, building APIs and services, and developing data pipelines that ensure reliable, fast, and observable operations. This is a hands-on build role where you will take ambiguous problems, make design decisions, ship to production, and mentor other engineers.

$250k - $500k