RL Environment Engineers: Building Tool Gyms For Knowledge Work

Terac is building a global pool of vetted human experts for AI research, labs, and product teams. The company is seeking an RL environment engineer to build and test tool-based simulation environments for knowledge work, support reinforcement learning training pipelines, and refine environment designs through technical feedback and model performance.

Responsibilities:

• Design and implement tool-based environments for knowledge work simulations
• Write clean and modular code to support reinforcement learning training pipelines
• Troubleshoot and refine environment mechanics based on testing feedback
• Collaborate asynchronously and participate in remote progress check-ins

Requirements:

• Professional experience as a machine learning or reinforcement learning engineer
• Hands-on background building custom RL environments or tool gyms
• Ability to commit to approximately 20 hours of work per week
• Comfortable discussing technical architecture and implementation strategies