Software Engineer, RL Data

Strong software engineering skills and proficiency in at least one modern programming language — we mostly use Python and TypeScript, and care more that you pick new tools up quickly than that you know our exact stack

Experience designing, building, and running backend systems or infrastructure

Effective use of AI tools in your own day-to-day work

Willingness to own problems end-to-end, including the parts that aren't engineering

Experience building LLM-powered systems: prompt pipelines, evals, or products with models in the loop

Experience with reinforcement learning on LLMs: creating environments, rewards, graders, or training data

Anthropic's RL Data team builds the systems that produce high-quality reinforcement learning data for Claude: data collection pipelines, human feedback tooling, the execution environments RL tasks run in, and the quality assurance that keeps training data trustworthy at scale.

Our goal is to make Claude genuinely great at complex, real-world work — and to point those capabilities at the things that matter most, including AI safety research and beneficial deployments of AI.

(To be upfront: this is dual-use work — it advances general capabilities too, though we aim to differentially advance the beneficial ones.)

Some weeks you'll be deep in pipeline or infrastructure engineering; others you'll be tuning prompts until the output is good, or sitting with a research team that depends on your systems and shipping the fixes they need.

Own significant parts of our stack end-to-end, from technical architecture through the unglamorous operational work that makes it succeed

Build data collection pipelines, read the transcripts they produce, and iterate on prompts, evals, and graders until the output is good