Note: The job is a remote job and is open to candidates in USA. The company is a fast-growing applied AI research lab that builds reinforcement-learning environments and agents for leading AI labs. The RL Environment Software Engineer will build simulated real-world workflows and agents, collaborate with research teams to identify future environment needs, and own the backend and infrastructure required for reliable, scalable systems.
Responsibilities
- Design and build high-quality RL environments that simulate real working environments end to end
- Develop agents for the tasks within those environments and iterate until they are efficient and production-ready
- Partner with the research team to scope which environments to build and why, staying ahead of future demand rather than only meeting present needs
- Own the backend and infrastructure layers that make environments reliable and scalable
- Help set engineering standards for a zero-to-one team as the RL function grows
Skills
- Strong machine-learning engineers who code heavily and build systems from scratch, with strong intuition for reinforcement learning
- Proficiency across a modern stack, Node.js and Python on the backend and React/TypeScript on the frontend, with strong Kubernetes and Docker skills
- Comfort operating in a fast-paced startup environment with high ownership and long hours
- A track record of meaningful tenure and impact at previous companies
- Bachelor's degree in computer science or a related technical field, or equivalent practical experience
- Reinforcement-learning experience or an RL research background is a strong plus, though not required
Benefits
- ~$400K+ OTE (uncapped profit share)
- Remote work arrangement in the United States
- A clear path to grow alongside the RL team as the function scales into industry pods
Company Overview