Research Engineer, Machine Learning (RL Velocity)

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The RL Velocity team owns the efficiency and reliability of Anthropic's RL Science stack — the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you will build and improve the core platform that underpins RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader organization 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

Requirements

• Strong software engineering fundamentals and a track record of building performant, reliable systems
• Experience working on ML infrastructure, distributed systems, or research tooling
• Comfortable operating across the stack, from low-level performance work to RL algorithms
• Bias toward shipping and iterating quickly, with high agency and low ego
• Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience
• Minimum years of experience: will correlate with internal job level requirements for the position

Strong candidates may also have (Nice-to-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

Compensation

Annual Salary: $500,000 - $850,000 USD

Logistics

• Remote-Friendly (travel required); offices listed: San Francisco, CA and New York City, NY
• Location-based hybrid policy: currently, staff are expected to be in one of Anthropic's offices at least 25% of the time
• Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist, though not all roles/candidates can be successfully sponsored

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Office space for collaboration

How we're different

• Focus on large-scale, high-impact AI research as a single cohesive team
• Emphasis on collaboration, communication, and research discussions
• Research directions include areas such as GPT-3, interpretability, scaling laws, and learning from human preferences