Job Description:
• 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.
Requirements:
• 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.
• Reinforcement-learning experience or an RL research background is a strong plus, though not required.
• Bachelor's degree in computer science or a related technical field, or equivalent practical experience.
Benefits: