Coding RL Engineer

About the Role

Join an early-stage AI company as a Coding RL Engineer, working with the reinforcement learning team to build coding environments and tasks for training and evaluating advanced models. You will turn real-world software engineering work into reproducible benchmarks that help improve coding AI.

What You'll Do

• Convert licensed production codebases into reproducible, containerized coding environments.
• Use issues, pull requests, commit histories, and incident records to create tasks covering bug fixes, features, refactors, testing, and multi-file agent work.
• Build and improve verifiers with hidden tests, rubric-based or model-based grading, and safeguards against reward hacking and answer leakage.
• Run model rollouts, review traces, and repair or remove tasks that are broken, ambiguous, too easy, or exploitable.
• Contribute tasks and analysis to coding benchmarks and build tools that speed up task creation and validation.
• Work with research teams to calibrate task difficulty and benchmark coverage.

What We're Looking For

• At least 2 years of professional software engineering experience delivering software systems.
• Very strong Python skills and fluency in another language such as TypeScript, Go, Java, or Rust.
• Hands-on Docker experience and familiarity with reproducible build and test environments.
• Experience navigating unfamiliar, complex codebases and getting them building, running, and tested.
• Working knowledge of coding model training and evaluation, including SWE-bench-style tasks, code evaluations, RLVR, and agent harnesses.
• Experience creating coding tasks from real engineering work and hardening verifiers against flaky tests, unclear requirements, and leaked solutions.
• Relevant experience with frontier AI labs, evaluation teams, RL environments, coding agents, or large enterprise and legacy codebases is helpful.
• Location
• Remote within the United States or in person in San Francisco, California.