RL Environment Software Engineer

The Opportunity

Compensation

• The advertised base compensation is $180,000 to $220,000 per year.
• The role offers approximately $400,000 or more in on-target earnings through uncapped profit sharing.

Workplace

• The role is remote within the United States.
• The work model is remote.

About the Company

Responsibilities

• Design and build high-quality reinforcement-learning environments that simulate real working environments end to end.
• Develop agents for 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.
• Anticipate future demand for reinforcement-learning environments 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 reinforcement-learning function grows.

Requirements

• Be a strong machine-learning engineer who codes heavily and builds systems from scratch, with strong intuition for reinforcement learning.
• Demonstrate proficiency with Node.js and Python on the backend, React and TypeScript on the frontend, Kubernetes, and Docker.
• Be comfortable operating in a fast-paced startup environment with high ownership and long hours.
• Have a track record of meaningful tenure and impact at previous companies.
• Reinforcement-learning experience or an RL research background is advantageous but not required.
• Hold a bachelor's degree in computer science or a related technical field, or have equivalent practical experience.