Reinforcement Learning Engineer Locomanipulation
HumanoidVisit Humanoid website
UK-based AI and robotics company building commercially scalable humanoid robots for industrial deployment.
London, United Kingdom
Funding history
About Humanoid
Humanoid develops industrial humanoid robots and its proprietary KinetIQ AI framework for real-world tasks across manufacturing, logistics, and related environments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design, train, deploy, and evaluate reinforcement learning policies for humanoid locomotion and locomanipulation. You will build simulation and training pipelines, design rewards and curricula, improve sim-to-real transfer, and integrate policies into the robot control stack.
Requirements
- Reinforcement learning experience
- Robotics or physical-systems reinforcement learning experience
- Experience deploying learned policies on real robotic systems
- Physics-based simulation experience
- Python or C++ programming
- MS or PhD in Robotics, Machine Learning, Computer Science, or a related field
Responsibilities
- Design and train reinforcement learning policies for humanoid robot control
- Build scalable simulation and training pipelines
- Design reward functions, observation spaces, and curricula
- Improve policy robustness and sim-to-real transfer
- Deploy and evaluate policies on real robotic systems
- Integrate policies into the control stack
Benefits
- 23 days of annual leave
- 15 days of paid sick leave
- Paid company holidays
- Private healthcare
- Equity
- Pension scheme with 8% total contribution
- Free daily breakfast, catered lunch, and snacks