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
Develop and improve QA frameworks to catch reward hacking and ensure environment quality
Build interfaces that make collecting human data fast and painless for the people providing it
Harden execution environments — sandboxing, snapshotting, tool coverage — so tasks hold up at training scale
Embed with the teams and domain experts who use our systems day-to-day: design pipelines and evals with them, support them directly, and ship the improvements they need
Work with operations, security, and compliance partners to roll our systems out to new users, and manage technical relationships with external data vendors

Strong software engineering skills and proficiency in at least one modern programming language
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
Proactive, open communication: you can be trusted to run a workstream, and to escalate early when something's off
Comfort iterating quickly in ambiguous, fast-changing situations
Care about the societal impacts of your work

Software Engineer, RL Data

Key skills