Humanoid is the first AI and robotics company in the UK, creating the world’s most advanced, reliable, commercially scalable, and safe humanoid robots. Our first humanoid robot HMND 01 is a next-gen labour automation unit, providing highly efficient services across various use cases, starting with industrial applications.
At Humanoid we strive to create the world’s leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity.
About the Role
We are looking for a Senior/Staff Robot Controls Engineer to develop whole-body control systems for bipedal robots. In this role you will work on a control stack combining whole-body and reinforcement learning, enabling robust loco-manipulation behaviors on real robots. You'll ensure that learning-based policies operate safely within structured control architectures, maintaining stability, predictability, and reliable deployment on hardware.
You will design and deploy control algorithms that run directly on physical robots, iterating between simulation and hardware experiments. You will also help shape the architecture of the robot control stack, defining how learning-based policies integrate with whole-body control and safety mechanisms.
In collaboration with colleagues across Boston, London, and Vancouver, you will tackle hard problems related to dynamic locomotion, contact-rich manipulation, balance recovery, and safe integration of learning-based behaviors.
What You’ll Do:
* Design safe whole-body control architectures for bipedal robots.
* Develop controllers enabling stable locomotion and loco-manipulation.
* Integrate reinforcement learning policies within the control stack, ensuring safe operation and reliable hardware behavior.
* Define interfaces between learned policies and structured controllers, enabling supervision and fallback mechanisms.
* Validate controllers in simulation and on physical robots.
* Contribute to a robust, modular real-time control codebase.
We’re Looking For:
* MS or PhD in Robotics, Control, Computer Science, or a related field.
* Experience developing control systems for complex robots, ideally legged or humanoid platforms.
* Experience with whole-body control or physics-based robot control architectures.
* Experience implementing reinforcement learning for robotic systems.
* Strong understanding of robot dynamics, kinematics, and multi-contact interaction.
* Strong C++ development skills for real-time robotic systems.
Nice to have:
* Experience with bipedal locomotion or loco-manipulation.
* Experience with safe RL approaches (e.g., constrained RL, safety filters, supervised policies).
* Background in trajectory optimization, motion generation, or MPC.
* Experience with real-time robotics middleware (e.g., ROS2).