Software Engineer, RL Environments

Responsibilities

• Build platforms for creating realistic and diverse reinforcement-learning environments at scale.
• Design end-to-end factories that transform large, heterogeneous raw datasets into training-ready environments.
• Define and automate consistent quality standards for vendor, tutor, acquired, and synthetic data.
• Create self-serve APIs and developer tooling for internal teams and external contributors.
• Partner with research, platform, and external teams to translate model-capability goals into training tasks and environments.
• Own open-ended engineering problems across research, data, and platform functions.

Requirements

• Strong software engineering fundamentals.
• Experience with data platforms, developer tools, distributed systems, or ML infrastructure.
• Ability to convert ambiguous quality standards into concrete automated checks.
• Experience building repeatable pipelines from messy, heterogeneous data.
• Interest in model behavior and the ability to translate capability goals into tasks and experiments.
• Strong cross-disciplinary collaboration and end-to-end ownership.