Reinforcement Learning Engineer - Locomanipulation

📋 Description

• Design and train RL policies for humanoid robot control.
• Build scalable simulation/training pipelines (e.g., Isaac Lab, MuJoCo).
• Develop reward functions and curricula for complex behaviors.
• Improve robustness and sim-to-real transfer for hardware deployment.
• Deploy and evaluate policies on real robotic systems.
• Integrate policies into the robot control stack.

🎯 Requirements

• MS or PhD in Robotics, ML, CS, or related field.
• Strong RL experience (PPO, SAC, offline RL).
• Experience applying RL to robotics or physical systems.
• Experience deploying policies on real robots.
• Experience with physics-based sims (Isaac Lab, MuJoCo).
• Strong Python and/or C++ programming skills.

🎁 Benefits

• 23 days annual leave, 15 days paid sick leave, holidays.
• Fully funded UK healthcare for employees.
• Equity in the company.
• 8% pension contribution (5% employee, 3% employer).
• Free daily breakfast, lunch, and snacks in-office.
• Collaborative environment with top engineers in AI and robotics.