Machine Learning Jobs

The Robotic Visual Perception and Learning research group at NVIDIA is seeking highly motivated PhD students for research internships. This role focuses on pushing the boundaries of computer vision, robotics, and machine learning with real-world impact. Interns will have the opportunity to publish their work in top-tier conferences and collaborate with experienced mentors, with carefully crafted projects tailored to their expertise.

$0k - $0k

Harvey is transforming legal and professional services by combining frontier agentic AI with an enterprise-grade platform. As we scale rapidly and take on increasingly complex use cases, we are expanding our engineering team to accelerate our ability to ship fast, delight users, and build infrastructure that scales with us. As an Engineering Manager for AI Platform, you will lead and scale a team of engineers building the foundational systems that power AI across Harvey. This includes model access and routing, agent and workflow orchestration, evaluation frameworks, tool and context infrastructure, and the observability needed to run LLM-powered products reliably at scale. You will partner with Product, Research, and product engineering teams to turn fast-moving advances in applied AI into durable, reusable platform capabilities and set the technical direction for how teams across Harvey build, test, and ship AI features. This role requires both technical depth and product intuition, with a focus on making fast, high-quality decisions, working at the cutting edge of applied AI, and growing a team that embodies engineering excellence.

$272k - $355k

Anthropic

The Cybersecurity RL team within Horizons is seeking a Research Engineer to advance the capabilities of AI models in secure coding, vulnerability remediation, and defensive cybersecurity. This role combines research and engineering, involving the design and implementation of RL environments, conducting experiments, delivering work into production training runs, and collaborating with cross-functional teams. The ideal candidate will possess domain expertise in cybersecurity and an interest in training safe AI models, potentially coming from backgrounds such as white hat hacking, security engineering, or detection and response.

$500k - $850k

Anthropic

The Interpretability team at Anthropic is dedicated to reverse-engineering how trained models work, believing that a mechanistic understanding is crucial for making advanced AI systems safe and steerable. This role focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms, akin to performing "biology" or "neuroscience" on neural networks. The team has made significant progress in understanding issues like "superposition" and decomposing models into interpretable components, with recent work identifying millions of features in production models and developing methods to understand multi-hop reasoning and planning. This research is foundational for building reliable, interpretable, and steerable AI systems and often involves collaboration with other teams at Anthropic to enhance AI safety.

$350k - $850k

As a member of the AI Gateway Team, you will be responsible for developing and enhancing our AI Gateway platform, which provides a unified API for accessing hundreds of AI models from multiple providers. You will collaborate with a remote and distributed team of engineers to build reliable, low-latency systems that handle rate limiting, intelligent failovers, and seamless integrations, enabling developers to ship AI-powered applications without managing provider-specific complexities. This role focuses on ensuring production-ready reliability for AI workloads, including automatic fallbacks during outages and consistent performance across providers like OpenAI, Anthropic, Google, and more.

$196k - $294k

Vercel is seeking a Machine Learning Engineer for its Trust & Safety Engineering team. This role focuses on building and operating production systems to detect and prevent platform abuse at scale. It's an engineering-intensive position, with approximately 80% of the time dedicated to writing and deploying production code, including services, pipelines, and infrastructure, and 20% focused on modeling. The goal is to take detection and classification approaches from initial prototypes to robust, production-ready systems.

$208k - $312k

Mirage is an AI video company focused on making creation dramatically easier by building multimodal agents that turn creative direction into edits, rendering engines that composite video and graphics, and generative video models. Our technology, including Captions (a creative workspace) and Tesseract (a video engine for AI agents), is now available more broadly through APIs. This role focuses on designing and building agentic systems that power creative workflows for short-form video, shaping how AI agents reduce friction, accelerate learning, and unlock new creative possibilities for users. You will experiment with emerging models and techniques to bring these experiences to life in production, working across product, machine-learning, and systems engineering to own problems end-to-end and help define how our agents are built and deployed.

$175k - $300k

Sygaldry Technologies is developing quantum-accelerated AI servers to dramatically speed up AI training and inference. By merging quantum computing with AI, the company aims to accelerate the development of superintelligence and ensure its efficient and affordable operation. Their unique approach involves integrating multiple qubit types into a single, fault-tolerant architecture to achieve the necessary cost, scale, and speed for advanced AI applications. Sygaldry is at the forefront of new discoveries in physics, engineering, and AI, tackling complex challenges with a grounded, optimistic, and rigorous culture. They are seeking individuals passionate about defining the future at the intersection of quantum and AI and driving its global impact.

$125k - $145k

Glean is seeking driven engineers to tackle cutting-edge challenges in data and AI security and governance. In this fast-paced startup environment, you will empathize with customer needs, research the domain, and devise novel solutions to complex problems. You will collaborate with product managers and designers to balance engineering constraints with requirements, delivering intuitive and reliable experiences for enterprises to ensure user safety.

$140k - $265k

Glean is seeking a Machine Learning Engineer to enhance the quality of its AI Assistant and autonomous agents. This role bridges production machine learning, LLM-powered systems, and product engineering, focusing on developing, evaluating, and refining assistant experiences for reliability and usefulness within enterprise workflows. You will tackle applied challenges in agent quality, evaluation, personalization, retrieval, and orchestration, with an emphasis on shipping production systems and improving the assistant's capabilities over time through enhanced signals, feedback loops, and end-to-end execution.

$180k - $205k

Glean is seeking software engineers to contribute to building a leading search and assistant product for the workplace. Engineers will work across the technology stack, focusing on areas such as generative AI, Retrieval Augmented Generation (RAG), query and document understanding, domain-adapted language models, natural language question-answering, and evaluation. The role involves close interaction with customers to understand their challenges and applying the most effective tools to solve them.

$175k - $270k

NVIDIA is seeking a graduate research intern to advance integrated sensing and communications (ISAC) on GPU-accelerated platforms. The intern will join a team building AI-native wireless systems and develop, train, and test ISAC algorithms end-to-end on the NVIDIA Aerial Testbed. This role is ideal for a student passionate about deep algorithm work and translating ideas into functional systems.

$0k - $0k

Salesforce is seeking a Software Engineering, AI Systems professional to join Salesforce AI Labs. This role involves building a product that learns from human demonstrations to automate complex workflows across enterprise applications. You will tackle challenging engineering problems related to agent dependability, reasoning, and error recovery. The position offers the opportunity to work directly with customers, own substantial systems from design to deployment, and contribute to taking a new offering from early adoption to general availability, supported by Salesforce's scale.

$149k - $224k

OpenAI

The Agent Post-Training team at OpenAI is responsible for developing the frontier agents that are shipped to users. This involves training models for products like Codex and ChatGPT, focusing on creating persistent, proactive intelligence that can operate computers, collaborate with humans and other agents, and expand user capabilities. The team defines the next generation of agent abilities, builds the training signals, and runs experiments to realize these advancements. The role specifically focuses on teaching models to operate computers, including navigating browsers and desktops, using tools, reasoning through complex workflows, and completing long-horizon tasks reliably. This position is at the intersection of frontier model training, product behavior, evaluation, and systems engineering, directly influencing the computer-use capabilities of OpenAI's future agents.

$380k - $500k

Prime Intellect is building the open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training for post-training at scale, including SFT, RL, tool use, and agent workflows. They are focused on open-source models trained for long-horizon tasks and the platform used to build them. The company has raised significant funding from prominent investors and is seeking individuals to work at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category.

$150k - $300k

Prime Intellect is building an open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, unifies compute, environments, evaluations, and training for post-training at scale, including SFT, RL, tool use, agent workflows, and continuous model improvement. They are focused on open-source models for long-horizon tasks and the platform their research team uses. The company has raised significant funding from prominent investors and is looking for individuals passionate about building at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category.

$150k - $300k

We are seeking a Lead Engineer, AI Agent Voice Experience to develop the next generation of AI-powered voice systems for contact centers. This role involves working at the intersection of speech, language, and real-time production systems to enhance how AI listens, understands, reasons, empathizes, and responds in live customer conversations. You will be responsible for developing and improving end-to-end machine learning systems for voice experiences, including automatic speech recognition, turn detection, agentic workflows, voice evaluation, text-to-speech, speech-to-speech models, and production optimization. Collaboration with researchers, product managers, designers, and engineers will be key to translating model improvements into measurable business impact. This position is ideal for individuals passionate about both model quality and production realities, focusing on rigorous evaluation, failure analysis, latency and robustness improvements, and shipping reliable, scalable real-time voice systems.

$205k - $270k

Deepgram is a leading platform for the Voice AI economy, offering real-time APIs for speech-to-text, text-to-speech, and building voice agents at scale. We empower over 1,300 organizations and 200,000 developers to create voice offerings powered by our advanced foundation models, accessible via cloud APIs or self-hosted solutions. Our AI-first approach means every team member is expected to actively use, experiment with, and build AI tools into their daily work, driving innovation and performance. We operate at the rapid pace of AI, requiring adaptability, continuous learning, and a proactive mindset to solve customer challenges and push technological boundaries.

$216k - $338k

Anthropic

Anthropic is seeking Software Engineers to join the Memory & Search team, responsible for how Claude remembers users and finds information across Claude.ai, Cowork, and Claude Code. This role involves both user-facing experiences, such as how memory is displayed and edited, and the underlying infrastructure for memory services, indexing, retrieval, and vector search. The team has recently transitioned memory to a dynamic, editable system unified across products, and improved search functionality significantly. The focus is now on developing compelling product features that leverage memory and search, requiring engineers with experience in shipping user-facing products at scale, a strong sense for product quality, and expertise in building agentic systems where models, tools, and user interfaces collaborate. You will drive product experiments, analyze usage, and contribute to the team's product-centric approach. This role also involves close collaboration with product, design, privacy, legal, and safeguards teams to ensure features meet privacy and enterprise requirements.

$405k - $485k

Alpaca is seeking a Senior Data Scientist, AI Evaluation to lead the measurement of our AI models and agents. In this senior individual contributor role, you will transform ambiguous quality questions into reliable ground truth, scoring methods, and evaluation loops that drive company-wide improvements. You will leverage an existing data foundation to enhance quality and accelerate the safe rollout of AI systems, owning the quality bar independently. This role is ideal for someone passionate about the correctness of AI outputs as much as their generation, who can partner with Product, Engineering, Analytics Engineering, and business stakeholders to define success, build robust evaluations, and ensure feedback loops drive iteration. If you have a strong quantitative background, a proven track record of rigorous, measurable work in evaluation, experimentation, or model validation, and desire ownership of a new evaluation practice at a rapidly growing financial services infrastructure company, we encourage you to apply.