Research Engineer, Machine Learning (RL Velocity)

Posted yesterday

anthropicNew York (NY)

Computer and Information Research Scientists Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)

SENIORITY

Lead

SALARY

$500,000 per year

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About the role

Research Engineer, Machine Learning (RL Velocity) Remote-Friendly (Travel-Required) | San Francisco, CA | New York City, NYAbout the role The RL Velocity team owns the efficiency and reliability of our RL Science stack – the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the 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 organization to ship better models faster. This is high‑leverage work: small improvements to velocity compound across every researcher and every run.

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 re‑architecting when needed
Partner closely with researchers and adjacent engineering teams (inference, sandboxing, etc.) 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 infrastructure in a fast‑moving environment$500,000 – $850,000 USDLocation and Logistics

Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience Location-based hybrid policy: Expect all staff to be in one of our offices at least 25% of the time. Some roles may require more office time.

Visa sponsorship: We sponsor visas when feasible and will make reasonable efforts to secure one for an offer recipient.

Benefits: Competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space to collaborate with colleagues. Equal Employment Opportunity As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

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