Job description
What We're Researching
We're hiring an RL environment engineer to help build tool-based environments, commonly known as tool gyms, for knowledge work applications. This paid engagement focuses on creating robust simulation frameworks where models can learn to interact with complex software tools. The resulting environments will directly support advanced reinforcement learning research and training pipelines.
How It Works
You will spend approximately 20 hours per week developing and testing new tool environments. This involves writing code to simulate various knowledge work tasks, ensuring realistic and stable agent interactions. You will also participate in remote video check-ins to discuss architecture decisions and troubleshoot implementation blockers. Throughout the project, you will iterate on environment designs based on model performance and technical feedback.
Who This Is For
We are looking for specialized machine learning professionals with hands-on experience in reinforcement learning environments. We welcome RL engineers, AI researchers, simulation developers, and machine learning infrastructure specialists. Ideal candidates have previously built or maintained custom gyms and are comfortable committing to a part-time weekly schedule.
What You'll Do
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.
Who Should Apply
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
Compensation
$120 per hour
Ready to participate?
Start your paid interview now
About Terac
Terac is building the world's largest pool of vetted human experts for AI. Researchers, AI labs, and product teams use Terac to recruit, screen, and pay study participants across industries, languages, and skill sets.
Learn more at or on YouTube at @jointerac.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.