Remote Reinforcement Learning Environment Engineer

Terac; United States; Remote; USD 102,000 - 146,000; Full time

Job summary

Terac in the United States is seeking AI researchers and machine learning engineers to participate in building worlds within a reinforcement learning platform. This role centers on designing and constructing scenarios for RL agents in complex, simulated environments and on refining the tools and interfaces used to create robust testing setups.

You will document your workflow, outline friction points, and prepare to share feedback during an interview about the platform's usability.

Qualifications

• Hands-on experience in simulation design and reinforcement learning environments.
• Experience with RL frameworks and training environments.
• Ability to configure platform interfaces and define agent scenarios.

Responsibilities

• Design and build specific scenarios within a remote reinforcement learning platform
• Configure environmental parameters and define agent interaction rules
• Test initial agent behaviors to validate your scenario structure
• Walk us through your workflow and highlight areas for platform improvement

Skills

RL/simulation design

Platform interfaces

Reward structures

Machine learning research

Job description

Terac in the United States is seeking AI researchers and machine learning engineers to participate in building worlds within a reinforcement learning platform. This role centers on designing and constructing scenarios for RL agents in complex, simulated environments and on refining the tools and interfaces used to create robust testing setups.

You will document your workflow, outline friction points, and prepare to share feedback during an interview about the platform's usability.