Staff Software Engineer, Code RL

Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant Python code

A track record of designing intuitive, safe APIs or frameworks that other engineers or teams adopted and built on

Demonstrated ability to anticipate failure modes — especially silent ones — and prevent them structurally through system design, type safety, and testing

Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows

Familiarity with reinforcement learning concepts, agentic systems, or LLM training pipelines

Experience building or operating large-scale distributed systems

Code RL at Anthropic drives reinforcement learning efforts behind Claude's coding capabilities, creating and scaling agentic coding environments.

This is an engineering role with unusual latitude to set technical direction and standards.

You'll be part of a team solving the engineering side of research efforts such as embedding with research teams, getting up to speed on their systems and needs, and designing the frameworks, APIs, and infrastructure that let researchers move faster, then rotating off, leaving behind well-oiled systems those teams can understand, own, and maintain themselves.

Your remit also includes the ongoing health of production RL runs: maintainable, monitored, and straightforward to triage.

The team's problem space spans the client side of sandboxed execution for agentic RL environments, large-scale data processing jobs, the lifecycle of production datasets, and the frameworks researchers build environments on.

You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and hard-won intuition for how complex systems fail — especially silently.