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.

We design robots in simulation before building them in hardware
.

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.

• 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.

• 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 (Mu Jo Co , 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.

• 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.