Robotics ML Expert, AI

📋 Description

• Design, build, and iterate on MuJoCo simulation environments for robotics research and AI training
• Implement and tune RL algorithms (PPO, SAC, TD3) to train agents on simulated tasks
• Define reward functions, observation spaces, and action spaces that produce robust, transferable policies
• Debug and optimize physics simulations — contact models, actuator dynamics, scene configs
• Evaluate trained policies for stability, generalization, and sim-to-real transfer potential
• Document environment specs, training procedures, and experimental results clearly

🎯 Requirements

• Strong hands-on experience with MuJoCo (or via dm_control, Gymnasium-Robotics)
• Solid understanding of RL theory and practical training pipelines
• Proficient in Python + ML frameworks (PyTorch or JAX)
• Experience defining reward functions for complex robotic tasks
• Familiar with robot kinematics, dynamics, and control fundamentals
• Can read and write MJCF/XML model files and understand their physics implications

🎁 Benefits

• Location: Fully remote — work from anywhere on the accepted locations list
• Compensation: $30–$70/hr based on location and seniority
• Hours: 15–40 hrs/week, hours vary by project
• Payment: Weekly via PayPal or Stripe