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About the Role
The Manipulation team is central to Humanoid's operations, focusing on whole-body locomotion and manipulation using imitation learning and RL on real robots. This senior or staff individual contributor role emphasizes deploying policies that work on physical robots, with results shared via blog posts rather than academic papers.
Responsibilities
- Post-train manipulation policies with behavior cloning and RL, owning the full loop from raw data to deployment on a real robot.
- Collaborate with the simulation team to set up RL training on a digital twin, iterating on reward design and simulation quality for reliable sim-to-real transfer.
- Partner with the Data Collection organization to drive data collection, defining data quality standards, ensuring diversity and coverage, and iterating on operator instructions.
- Design data preprocessing strategies to enhance the quality of collected data.
- Expand observation and action spaces to support new capabilities and collaborate with the Teleoperations team to expose them to robot operators.
- Work with Controls teams to improve motion smoothness and the teleoperation experience.
- Provide feedback on current hardware limitations to inform future hardware design cycles.
- Collaborate closely with the pre-training team to adapt research advancements for reliable use in real-world industrial demonstrations.
Requirements
- 3+ years of experience working on robots in industry or research with demonstrable shipped work.
- Hands-on experience with modern manipulation methods, preferably near production deployment.
- Solid understanding of modern teleoperation and low-level robot control stacks.
- Experience with neural network post-training, specifically behavior cloning and RL applied to physical systems.
- Familiarity with deep learning infrastructure including streaming datasets, checkpointing, distributed training, and PyTorch or JAX.
- Proficiency in profiling and debugging numerics.
- Strong software engineering and coding fundamentals, including maintainable research code, clear experiment documentation, and concise communication of trade-offs.
- Preparedness for a LeetCode-style coding round.
- A drive to get things working on the robot, with an instinct for debugging issues.
- Proactive approach to tackling open problems without waiting for detailed specifications.
- Working English proficiency.
Skills
- Behavior cloning
- Reinforcement Learning (RL)
- Sim-to-real transfer
- Data preprocessing
- Deep learning infrastructure
- PyTorch
- JAX
- Software engineering
- Coding fundamentals
- Teleoperation
- Low-level robot control
Location
- London, UK
Work Type
- On-site
- Full-time
Experience Level
- Senior
- Staff
Education Level
- PhD
- Postdoc
Salary/Compensations
- A wide range, set by the level shown in interviews
Benefits
- Stock options with meaningful upside
- 30+ paid days off (23 days annual leave, UK bank holidays, company shutdown)
- Fully funded private healthcare (virtual and in-person care, mental health support)
- Pension (8% total contribution)
- Daily food (free breakfast, catered lunch, snacks)
- Real ownership with direct access to founding leadership
- Visa sponsorship
- Relocation to London
About the Company
- Humanoid is building highly capable, commercially scalable, and safe humanoid robots.
- Its platform, HMND-01, is deployed in industrial environments, positioning Humanoid as a leading humanoid robotics company in Europe.
- The company has over 300 employees from 34+ nationalities, fostering a flat structure where decisions directly impact real robots.
- Offices are located in London (HQ), Boston, Vancouver, and San Diego.
- Humanoid is well-funded, experiencing rapid and deliberate growth.
- Company values include Speed, Ambition, Passion, and Trust.