Similar Jobs
See allRL Environment Engineer
Terac
Global
Reinforcement Learning
Machine Learning
Python
Member of Technical Staff - RL Environments
Cohere
Global
Python
Reinforcement Learning
AI Agents
AI Research Scientist - Reinforcement Learning for Agent Training
Niural
Python
Machine Learning
Reinforcement Learning
Finance Professionals: Scenario Building for AI Environments
Terac
Global
Finance
Accounting
Financial Modeling
AI Trainer – Mechanical Engineers – CAD Expertise (Remote Advisory)
Prolific
Switzerland
Mechanical Engineering
CAD
Python
What We're Researching:
- Hiring AI researchers and ML engineers to build worlds within a reinforcement learning platform.
- Work directly influences how agents interact with complex simulated environments during training.
- Your technical expertise refines tools and interfaces for robust testing scenarios.
How It Works:
- Connect to a remote platform to design and construct specific RL scenarios.
- Configure environmental parameters, define spatial constraints, and run preliminary agent interactions.
- Document your workflow and highlight friction points for platform improvement.
Who This Is For:
- Professionals with hands-on experience in simulation design and RL environments.
- Ideal for ML engineers, AI researchers, simulation developers, or technical game designers.
- Must be comfortable configuring complex platform interfaces and defining structured agent scenarios.
What You'll Do:
- Design and build specific scenarios within a remote RL platform.
- Configure parameters and define agent interaction rules.
- Test initial agent behaviors and walk through your workflow for feedback.
Terac
Terac is building the world's largest pool of vetted human experts for AI. They provide a platform for researchers, AI labs, and product teams to recruit, screen, and pay study participants across industries.