Find your next AI engineering role.

Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. This role is for a founding member of the Multi-Embodiment Generalist Agent (MEGA) team, focused on building foundation models for general-purpose robots. These models will learn from large-scale video, language, and robot-interaction data to generalize across tasks and embodiments, enabling agents to perceive, reason about, and act reliably in the physical world. The work combines frontier ML research with direct real-world evaluation on a growing fleet of robots.

$311k - $420k

Anthropic

Our team studies how large teams of agents scale to solve complex problems that a single agent cannot, such as rewriting major codebases or formalizing mathematics. We investigate the impact of increasing agent numbers, compute budget, and task length on performance, cost, and coordination. This role bridges research and engineering, involving designing and running large experiments, building the necessary systems, and analyzing surprising results. We aim to move quickly from vague questions to running experiments, developing the platform and evaluations Anthropic uses to measure and manage large agent teams.

$500k - $850k

ClickHouse

ClickHouse Labs is an applied research group focused on identifying and solving challenging problems in database systems, with a goal of advancing the state of the art and translating research into real-world system improvements. As a Research Scientist, you will tackle high-impact problems at the intersection of database systems, distributed systems, AI, and systems software engineering. You will collaborate with experienced researchers and engineers on a broad range of topics, including query optimization, execution engines, distributed systems, and emerging agentic workloads, working with leading open-source systems like ClickHouse and PostgreSQL. Your work will involve investigating performance bottlenecks, developing new algorithms and system designs, and evaluating them under realistic conditions, with opportunities to publish your work and contribute to open-source projects.

$175k - $235k

Percepta

Percepta is transforming critical institutions with applied AI, embedding with industry-leading customers to drive AI transformation. We bring together forward-deployed expertise in engineering, product, and research, along with our in-house toolkit for rapidly deploying agentic workflows and strategic partnerships. As a Research Scientist - Reinforcement Learning, you will work at the intersection of RL research and real-world deployment, advancing decision-making capabilities for critical industries. You will collaborate closely with Embedded Product Managers and engineers to ensure our solutions transform how companies operate.

$200k - $400k

As an intern, you will help develop and optimize our AI training platform by improving data processing pipelines, accelerating model training and inference workflows, and/or enhancing testing infrastructure. You will support tool development, instrumentation, and system monitoring to boost reliability, reduce latency, and increase iteration speed for advancing autonomous driving performance. This role is part of GM's AV/AI Platform organization, which builds the software foundation and engineering tools that power safe, reliable, and scalable autonomous driving and advanced driver-assistance systems.

$97k - $142k

Wayve is seeking a founding Research Scientist to join the Multi-Embodiment Generalist Agent (MEGA) team. This role focuses on building foundation models for general-purpose robots beyond self-driving vehicles, creating intelligent agents capable of perceiving, reasoning, moving, and manipulating the physical world across diverse embodiments. You will play a senior, high-impact role in defining the research agenda, technical strategy, and foundations of a new robotics program. The work involves the entire robot-learning stack, from scalable data flywheels and new model architectures to training large models, designing evaluations, and deploying policies on real robots. You will collaborate with researchers, ML engineers, and roboticists to advance ambitious ideas from research hypotheses to large-scale experiments and real-world capabilities.

$370k - $513k

Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. This role is within the Generative Simulation team, which advances autonomous driving research by incubating new ideas. As a Machine Learning Engineer, you will develop next-generation world models and planners, such as GAIA, to simulate complex driving environments for faster training, broader testing, and scalable deployment. A major focus is on efficiency and interactivity, requiring models to run thousands of roll-outs per second, support closed-loop agent interaction, and fit within practical compute budgets. You will work at the intersection of machine learning research, multi-modal modeling, and real-world deployment, tackling challenges like deploying autonomous vehicles without real-world data and assessing if synthetic environments can replace physical testing.

Moveworks is seeking an Agentic AI Harness Architect to define the technical vision for our agentic AI harness. This role involves planning, selecting tools, managing context, and implementing memory, critique, reflection, adaptation, and recovery mechanisms for AI agents. You will invent and prototype algorithms to enable agents to complete complex tasks with minimal supervision and high reliability. The position requires designing model-agnostic abstractions to integrate foundation models, specialized agents, enterprise tools, and workflows, while developing approaches for agent memory and learning that prioritize enterprise security and privacy. You will also create rigorous benchmarks and evaluation methods for agent performance and explore advanced methods like iterative planning, self-critique, and multi-agent coordination. The role includes building prototypes, identifying promising ideas, and collaborating with platform and product teams to bring them to production, while remaining hands-on with code and experiments.

$201k - $352k

As a PhD AI/ML Engineering Intern within General Motors’ Autonomous Vehicles organization, you will advance reliable AI/ML capabilities by translating deep research into validated, production-oriented systems. Your work may support perception, prediction, planning, decision-making, embodied AI, simulation, sensor understanding, mapping, or large-scale model development. You will work with real-world driving and sensor data, modern machine learning methods, and autonomous vehicle evaluation environments. You will collaborate with researchers and engineers to design experiments, build and assess models, investigate failure cases, and integrate promising approaches into broader AV systems.

$156k - $187k

HUD is seeking a Product Engineer to transform significant product challenges into tangible user experiences across its AI data platform and marketplace. This role involves collaborating with product, design, engineering, research, and go-to-market teams to identify user pain points in AI data creation and training, define product improvements, and develop solutions. The position blends product strategy, interaction design, and full-stack development, requiring the ability to translate complex technical workflows into clear and user-friendly interfaces while retaining necessary detail.

$100k - $225k

Handshake is seeking a Member of Technical Staff, Evals to help define how frontier AI systems are measured, understood, and improved. This is a high-ownership role for researchers who build, partnering with AI researchers, domain experts, and customers to develop new benchmarks, reward and verifier systems, agent-evaluation methodologies, and data-quality techniques. Early members of the team will have significant influence over technical direction, operating culture, and the open-source software, benchmarks, and research products built. The company prioritizes demonstrated research capability, technical judgment, and a builder's mindset over specific titles, degrees, or career paths.

$200k - $350k

As a Machine Learning Engineer II – Learned Behaviors, you will help develop and deploy behavior models that power decision-making for autonomous trucks. Working closely with teams across perception, prediction, planning, and safety, you will contribute to learned behavior modules that enable safe, efficient, and human-like driving in real-world freight operations. This role focuses on building, validating, and improving machine learning models and infrastructure that support learned behavior systems within the autonomy stack.

$153k - $184k

As a Senior Applied AI/ML Scientist on the Search team, you will shape the technical vision, machine-learning algorithm strategy, and system design behind Faire's Search functionality. You will advance real-time search and recommendation systems that power next-generation shopping experiences by working at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query. This is a chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, collaborating closely with a talented team of scientists and engineers.

$211k - $291k

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

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

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

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

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI trainers. We are a growing team of researchers, engineers, and operators backed by significant VC funding. We are seeking a Research Manager to lead research focused on enhancing HUD's agent training data and evaluations for frontier models. This role involves guiding research engineers through complex projects, translating findings into scalable methods, and staying technically engaged while ensuring rigorous experimentation and impactful results. The ideal candidate will possess a deep understanding of model training dynamics, including how signals, data, and evaluation design influence outcomes.

$120k - $295k

Snorkel AI

Snorkel AI is seeking a Research Scientist to advance the creation of high-quality data and environments for AI agents. You will build and optimize pipelines that integrate real-world data, automated generation, and human expert input. Collaborating with domain experts, academic partners, customers, and internal teams, you will scale these pipelines to address frontier model performance gaps and enhance data and environment diversity. Your work will empower human knowledge and judgment, enabling experts to refine data and agentic environments, solidifying Snorkel's position as a leader in frontier data solutions. This role is perfect for individuals passionate about advancing frontier AI through data and environment creation, and who enjoy translating research into scalable, reusable systems.

$200k - $375k

Our Consumer Bank AI Modeling team develops advanced analytics and machine learning solutions that inform high-impact decisions across field workforce effectiveness, customer engagement, and banker-led growth. As an Applied AI Modeling Vice President in this team, you will build and deploy advanced AI/ML models that measurably improve banker sales effectiveness and customer outcomes. Your models will help bankers deliver the right outreach at the right time to our customers, driving deposit growth, increasing customer retention, and strengthening relationships. You will operate in a highly governed environment and partner closely with product, UX, operations, and technology teams to translate modeling innovation into field-ready tools that bankers trust and adopt.

We are building the next generation of large-scale reinforcement learning based recommender systems and arbitration engines that will power personalized experiences across marketing, customer servicing, and digital products. This is a high-impact initiative central to our platform, leveraging rich credit and customer behavioral data from tens of millions of customers to deliver intelligent, real-time experiences across our digital experiences, including Mobile, Web, and Email. You will help shape a foundational system that reaches a vast portion of the U.S. population, influencing how millions of people discover, decide, and engage across financial and lifestyle experiences.

$179k - $205k

Applied Intuition

Applied Intuition is seeking a Software Engineer to join their Korea office and build multi-agent autonomy development tools for defense customers. This on-site role focuses on creating capabilities that enable the design, training, and validation of coordinated Unmanned Aerial Vehicle (UAV) behavior. The engineer will collaborate with the U.S. product engineering team and directly engage with Korean defense customers to translate their operational needs into product features. The position involves developing core features for autonomy tools, validating these tools with real-world UAV applications, defining the role of simulation in the development cycle, and contributing to system-level design and architecture.

$60k - $300k

Innodata is seeking a Research Scientist to lead the science of data for robotics foundation models. This role involves partnering directly with customers and frontier labs to define how data is designed, structured, and evaluated for next-generation AI systems in robotics. You will leverage scientific judgment to make high-leverage decisions about data capture, synthesis, representation, and evaluation, ensuring that the data collected and generated directly supports the development of robust and transferable AI models for manipulation, locomotion, vision-language-action, and world models.

$160k - $185k

Turing

Turing is seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

$250k - $400k

Anduril Industries

Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. We are seeking a Senior AI Infrastructure Engineer to build, scale, and optimize the end-to-end machine learning platform that powers our autonomous systems. In this role, you will own critical components of our ML platform and MLOps tooling, building and operating the infrastructure required to train, evaluate, host, and serve complex AI models across various environments. You will collaborate closely with AI Research Scientists and Platform Engineers to streamline model development, enhance hardware utilization, and ensure the reliable deployment of models into safety-critical operational settings.

$191k - $253k

Turing

Turing is seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

$250k - $350k

Turing

Turing is seeking exceptional Research Scientists to join our research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier evaluation, synthetic data, hallucination and reliability, and agentic science. We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them.

$250k - $400k

Turing

Turing is seeking exceptional Research Scientists to join our STEM research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science. We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them.

$250k - $350k

Turing

Turing is seeking exceptional AI Research Scientists to join our STEM research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science. We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them.

$150k - $300k