Robotics Simulation & Control 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.

As a Robotics Simulation & RL Engineer, you will help design and validate future generations of our robotic platforms - including bipedal and wheeled systems - using physics simulation and reinforcement learning. You will develop tools to determine whether a robot design can perform real-world tasks before committing to hardware. Your work will directly inform robot architecture, actuator selection, sensor placement, and control strategies. A key responsibility of this role is owning and validating the canonical robot models (URDF and simulation assets) used across simulation and control stacks.

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.

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.

Experience with whole-body control or torque-controlled robots; Experience with simulation-driven hardware design; Experience building large-scale RL training pipelines.

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.