Robotics Control Engineer -Locomotion

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.


Our Mission

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.

Vision

In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries. The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do. We believe that providing a universal basic income will eventually be a true evolution of our civilization.

Solution

As the demands on our built environment rise, labour shortages loom. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed. By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs.

We’re seeking a highly skilled Senior/Staff Control Engineer to take ownership of the locomotion control systems for our biped humanoid robots. You’ll be at the cutting edge of robotics, responsible for developing advanced control algorithms that balance precision, efficiency, and adaptability. This role focuses on designing robust controllers for walking, balancing while manipulating, fall recovery, and other advanced mobility tasks. The ideal candidate will have strong expertise in reinforcement learning (classic locomotion pipeline would be a plus).

Responsibilities

• Design and implement control algorithms (classic or RL-based policies) for locomotion tasks, including walking, balancing while manipulating, squatting, stair climbing, fall recovery, and other dynamic maneuvers.
• Model and simulate complex dynamics, taking into account robot kinematics, actuator limitations, and environmental interactions to optimize performance.
• Conduct rigorous testing in both simulated and real-world environments to validate algorithms and ensure robustness across various conditions.
• Work closely with software, hardware, and perception teams to integrate control strategies into the overall robotic system.

Expertise

• Master’s or PhD in Robotics, Control Systems, Mechatronics, or a related field.
• At least 2 years of experience in the design and implementation of control systems for biped robots, focusing on locomotion.
• Understanding of model predictive control (MPC), optimal control, and feedback control loops in dynamic robotic systems.
• Strong expertise in reinforcement learning for robotics
• Deep understanding of humanoid robot dynamics and balance control.
• Strong experience with hardware-in-the-loop testing and deployment on physical humanoid robots.
• Strong hands-on experience with robot simulation platforms such as Mujoco, Isaac Sim or similar environments.
• Proficiency in Python and C++ for algorithm development, testing, and deployment.
• Experience in topics like model-free RL, imitation learning, or hybrid control systems that combine classic and modern methods.

Desirable Skills and Experience

• Familiarity with real-time control systems and integration with hardware, including actuators and sensors.
• Familiarity in sensor fusion for state estimation (IMUs, joint encoders, force/torque sensors) to enable robust balance and locomotion control.
• Understanding of actuators dynamics and modeling
• Knowledge of dynamics and control of legged robots, including whole-body control, balance, and stability management (ZMP, capture point control, etc.).
• Proven experience in robotic system integration, including end-to-end validation of locomotion systems (joint to whole-body motion).
• Familiar with compliance testing, gait optimization, and energy efficiency evaluation for legged robots.

Benefits

• High competitive salary.
• 23 working days of vacation per year.
• Flexible working hours.
• Opportunity to work on the latest technologies in AI and Robotics.
• Startup model, offering a dynamic and innovative work environment.

How to Apply

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