Research Engineer, Machine Learning (RL Velocity)

About the Role

As a Research Engineer on the RL Velocity team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster.

Responsibilities

• Build and improve the RL training infrastructure that researchers depend on day-to-day

• Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed

• Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster

• Own the reliability and performance of research runs end-to-end

• Contribute to design decisions that shape how Anthropic does RL at scale

You May Be a Good Fit If You

• Have strong software engineering fundamentals and a track record of building performant, reliable systems

• Have worked on ML infrastructure, distributed systems, or research tooling

• Care about enabling other people's work and find leverage through platforms rather than individual experiments

• Are comfortable operating across the stack, from low-level performance work to RL algorithms

• Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego

Strong Candidates May Also Have

• Experience with large-scale distributed training (RL, pre-training, or post-training)

• Familiarity with JAX, PyTorch, or similar ML frameworks

• A track record of operating at the edge of research and infra in a fast-moving environment

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.

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• A lovely office space in which to collaborate with colleagues

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.

• 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.

Come Work With Us!

• Learn about our policy for using AI in our application process