Senior Machine Learning Research Engineer

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are looking for a strong Machine Learning Research Engineer to join our Autonomy team and develop the learning-based algorithms that power dynamic locomotion and whole-body control on our humanoid robots.

You will develop robust, reusable motion capabilities that enable the robot to move dynamically, maintain balance, interact with its environment, and combine locomotion with manipulation. This includes building the underlying learning-based motion primitives that can be composed into increasingly complex whole-body behaviors. You will work closely with robotics, controls, simulation, and machine learning engineers to turn learned behaviors into reliable capabilities running as part of the robot's real-time control stack.

WHAT YOU'LL DO - Design and evaluate new robot platforms using physics simulation; - Analyze robot capabilities including workspace, manipulability, dynamic balance, and torque limits; - Use reinforcement learning to stress-test robot designs and explore capability limits; - Own and maintain URDF models of current and future robot platforms; - Maintain the CAD → URDF → simulation pipeline; - Develop tools and benchmarks to evaluate locomotion, manipulation, and platform robustness; - Provide quantitative feedback to hardware teams on actuator sizing, joint placement, mass distribution, and sensor layout; - Collaborate with mechanical, control, and perception teams to guide platform design decisions.

WHAT WE'RE LOOKING FOR - M.Sc http://M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control, or a related field; - Strong foundation in robot kinematics and dynamics; - Experience with robot simulation environments (MuJoCo, Isaac Sim, Gazebo, or similar); - Experience with reinforcement learning in robotics or physics-based simulation; - Experience working with URDF or similar robot description formats; - Strong programming skills in Python and/or C++; - Experience training RL locomotion or manipulation policies.

Nice to have: - Experience with legged, humanoid, or wheeled robots; - Experience with whole-body control or torque-controlled robots; - Experience with simulation-driven hardware design; - Experience building large-scale RL training pipelines. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.