Research Engineer, Machine Learning (RL Velocity)

Overview

In this role you will help build and improve the RL training infrastructure that underpins Anthropic’s research program, removing bottlenecks and enabling researchers to ship better models faster. You’ll work closely with researchers and adjacent engineering teams to enhance reliability and performance across the RL stack. The role focuses on high-leverage platform work that scales impact across every research run. This is a hands-on position in a fast-moving, collaborative environment with a clear emphasis on shipping impactful tooling.

Pay / Benefits

• competitive compensation
• equity donation matching (optional)
• generous vacation and parental leave
• flexible working hours
• office space for collaboration

Responsibilities

• Build and improve the RL training infrastructure relied on daily by researchers
• Identify and remove bottlenecks across the RL stack via debugging, profiling, and rearchitecture
• Collaborate with researchers and adjacent engineering teams to ship faster, user-focused tooling
• Own the end-to-end reliability and performance of research runs
• Contribute to design decisions shaping how Anthropic does RL at scale

Key requirements

• Strong software engineering fundamentals and experience building performant, reliable systems
• Experience with ML infrastructure, distributed systems, or research tooling
• Bias toward enabling others and leveraging platforms over single experiments
• Comfort across the stack, from low-level performance to RL algorithms
• Entrepreneurial mindset with rapid shipping and iteration

• collaboration
• communication
• adaptability
• ML infrastructure
• distributed systems
• research tooling

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