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Senior Robotics control Engineer_Locomotion

JR United Kingdom

Telford

On-site

GBP 55,000 - 90,000

Full time

2 days ago
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Job summary

A pioneering AI and robotics company in the UK is seeking a highly skilled Staff Control Engineer. The successful candidate will develop advanced control algorithms for humanoid robots, focusing on locomotion and balance. This position offers a chance to work on cutting-edge robotics and contribute to transformative technologies in this rapidly evolving field.

Benefits

Highly competitive salary
23 working days of vacation per year
Flexible working hours
Opportunity to work on latest technologies
Dynamic and innovative work environment

Qualifications

  • Minimum 5 years of experience in control systems for biped robots.
  • Expertise in reinforcement learning applications for robotics.
  • Experience with hardware-in-the-loop testing.

Responsibilities

  • Design and implement control algorithms for locomotion tasks.
  • Conduct testing in simulated and real-world environments.
  • Collaborate with cross-functional teams on control strategies.

Skills

Model predictive control
Optimal control
Reinforcement learning
Balance control
Sensor fusion

Education

Masters or PhD in Robotics, Control Systems, or related field

Tools

Mujoco
Isaac Sim
Python
C++

Job description

Social network you want to login/join with:

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Client:

TTE Staffing

Location:

telford, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

3

Posted:

04.06.2025

Expiry Date:

19.07.2025

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Job Description:

About the Job

A pioneering AI and robotics company based in the UK is creating the worlds most advanced, reliable, commercially scalable, and safe humanoid robots. Their first humanoid robot, HMND 01, is a next-generation labor automation unit, delivering highly efficient services across various industrial use cases.

Our Mission

We strive to create the worlds 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, we believe in a future where humans and machines build a new era filled with knowledge, inspiration, and remarkable discoveries. The development of functional humanoid robots supports an era of abundance and well-being, where poverty disappears and people gain the freedom to choose their pursuits. The evolution toward universal basic income represents a true advancement of civilization.

Solution

As demands on our built environment grow and labor shortages loom, manufacturing, construction, and logistics industries face increasing pressure. By deploying general-purpose humanoid robots in hazardous or monotonous environments, our goal is to safeguard human well-being while addressing critical global labor gaps.

We are seeking a highly skilledStaff Control Engineerto take ownership of locomotion control systems for biped humanoid robots. This position is at the cutting edge of robotics and will be responsible for developing advanced control algorithms that prioritize precision, efficiency, and adaptability. The focus will be on designing robust controllers for walking, balancing during manipulation, fall recovery, and other advanced mobility tasks. The ideal candidate will have deep expertise in classic locomotion pipelines, whole-body control, and reinforcement learning.

Key Responsibilities
  • Design and implement control algorithms (classic or RL-based) for locomotion tasks such as walking, balancing while manipulating, squatting, stair climbing, and fall recovery.
  • Model and simulate complex dynamics, considering robot kinematics, actuator limitations, and environmental interactions.
  • Conduct rigorous testing in both simulated and real-world environments to validate algorithms.
  • Collaborate with software, hardware, and perception teams to integrate control strategies into the full robotic system.
Required Qualifications
  • Masters or PhD in Robotics, Control Systems, Mechatronics, or a related field.
  • Minimum 5 years of experience designing and implementing control systems for biped robots with a focus on locomotion.
  • Proficiency in model predictive control (MPC), optimal control, and feedback control loops.
  • Expertise in reinforcement learning applications for robotics.
  • Strong knowledge of humanoid robot dynamics and balance control.
  • Experience with hardware-in-the-loop testing and physical deployment.
  • Hands-on experience with simulation platforms like Mujoco, Isaac Sim, or similar.
  • Proficiency in Python and C++ for algorithm development and deployment.
  • Understanding of advanced RL topics (model-free RL, imitation learning, hybrid control).
  • Familiarity with real-time control systems, actuators, and sensors.
  • Experience in sensor fusion for robust balance and locomotion control (IMUs, encoders, force/torque sensors).
Preferred Qualifications
  • Understanding of actuator dynamics and modeling.
  • Deep knowledge of dynamics and control of legged robots (ZMP, capture point control, etc.).
  • Experience designing control algorithms for actuator-level performance (torque, force, impedance, etc.).
  • Familiarity with SEAs, harmonic drives, direct drive motors, and custom actuators.
  • Proven experience in full robotic system integration and locomotion validation.
  • Skilled in HIL and SIL simulation design for control testing.
  • Experience developing automated test frameworks for actuator and control system validation.
  • Knowledge of failure mode analysis, robustness testing, and actuator system identification.
  • Ability to validate and tune controllers on full-scale humanoid platforms in lab and field.
  • Experience with compliance testing, gait optimization, and energy efficiency evaluations for legged systems.
Benefits
  • Highly competitive salary
  • 23 working days of vacation per year
  • Flexible working hours
  • Opportunity to work on the latest technologies in AI, Robotics, Blockchain, and more
  • Startup model offering a dynamic and innovative work environment

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