Quick Summary
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.
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
~1 min readWe're hiring a Robotics Simulation & Control Engineer to join our Controls team based in London.
As a Robotics Simulation & Control 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.
Responsibilities
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Design and evaluate new robot platforms using physics simulation.
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Analyze robot capabilities including workspace, manipulability, dynamic balance, and torque limits.
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Use reinforcement learning to stress-test robot designs and explore capability limits.
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Own and maintain URDF models of current and future robot platforms.
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Maintain the CAD → URDF → simulation pipeline.
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Develop tools and benchmarks to evaluate locomotion, manipulation, and platform robustness.
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Provide quantitative feedback to hardware teams on actuator sizing, joint placement, mass distribution, and sensor layout.
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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 (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++.
Nice to have:
Experience with legged, humanoid, or wheeled robots.
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.
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- April 16, 2026
- First seen
- September 25, 2026
- Last seen
- September 25, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 27%
- Scored at
- September 25, 2026
Signal breakdown
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