Reinforcement Learning Engineer

📋 Description

• Architect sophisticated neural network topologies and RL algorithms for whole-body locomotion and
• Develop high-performance policies and training pipelines for deployment on physical hardware.
• Collaborate with hardware and controls teams to diagnose issues and enable complex learned

🎯 Requirements

• Hands-on RL experience (3+ years) with PyTorch or JAX and high-fidelity simulators (MuJoCo
• Strong Python for prototyping and C++ for performant deployment.
• Experience building large-scale distributed training pipelines and optimizing them.
• Deep understanding of RL, imitation learning, model-based RL, and sim-to-real transfer.
• Solid intuition for robot dynamics and controls theory.
• Proven track record deploying learning-based policies on physical robotics systems.