Research Engineer, Machine Learning (RL Velocity)

ABOUT THE ROLE Anthropic is a rapidly growing organization dedicated to creating reliable, interpretable, and steerable AI systems. Our mission is to ensure that AI is safe and beneficial for users and society as a whole. As a Research Engineer on the RL Velocity team, you will play a critical role in building and improving the core platform that underpins our RL Science stack. This high-leverage work will enable our researchers to iterate quickly on training runs, remove bottlenecks, and make it easier for the broader organization to ship better models faster. WHAT YOU'LL DO As a Research Engineer, you will be responsible for building and improving the RL training infrastructure that researchers depend on day-to-day. This includes identifying and removing bottlenecks across the RL stack, partnering with researchers and adjacent engineering teams to understand pain points and ship tooling that makes them faster, owning the reliability and performance of research runs end-to-end, and contributing to design decisions that shape how Anthropic does RL at scale. WHAT YOU'LL NEED To be successful in this role, you will need strong software engineering fundamentals and a track record of building performant, reliable systems. Experience with ML infrastructure, distributed systems, or research tooling is also highly desirable. You should be comfortable operating across the stack, from low-level performance work to RL algorithms, and have a bias toward shipping and iterating quickly. WHY REMOTE As a remote employee, you will have the flexibility to work from anywhere and be part of a team that is committed to creating beneficial AI systems. Our remote policy allows for a high degree of autonomy and flexibility, while also providing opportunities for collaboration and connection with colleagues. BENEFITS The annual compensation range for this role is $500,000 - $850,000 USD. We also offer a competitive benefits package, including a minimum education requirement of a Bachelor's degree or an equivalent combination of education, training, and/or experience. We sponsor visas for eligible candidates and have a location-based hybrid policy that requires staff to be in one of our offices at least 25% of the time.