Reinforcement Learning Engineer Manipulation
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 use reinforcement learning to build manipulation policies in simulation and on physical robots. You will create diverse simulated tasks, collect trajectories for behavior cloning, establish real-world training pipelines, and experiment with sim-to-real transfer approaches.
Requirements
- 3+ years building deep-learning systems
- LLMs, VLMs, or image and video generative models
- Reinforcement learning with deep neural networks
- Python
- PyTorch or JAX
- Profiling
- Numerical debugging
- Research-code development
- Experiment documentation
Responsibilities
- Train language-vision-conditioned manipulation policies using reinforcement learning
- Construct diverse manipulation-task suites in simulation
- Collect simulation trajectories for behavior cloning
- Establish real-world reinforcement-learning training pipelines
- Experiment with sim-to-real policy transfer
Benefits
- Stock options
- 30+ paid days off including 23 days of annual leave, UK bank holidays, and company closure days
- Private healthcare
- Pension scheme with 8% total contribution
- Free daily breakfast, catered lunch, and snacks in-office