R&D
Motion Control Engineer - Actuator Control Algorithms
About us:
Mobileye is a global leader in Physical AI, developing computer vision, software, and hardware to power autonomous driving solutions and humanoid robots. Our mission is to bring autonomy into the real world by building intelligent technologies that are designed to expand accessibility and enhance everyday life, from advanced driver assistance systems (ADAS) and autonomous driving to robotics and humanoids.
Built on decades of automotive innovation and industrial-scale AI expertise, Mobileye technologies power more than 230 million vehicles worldwide. With teams around the world, we continue to innovate at the forefront of autonomous systems, advancing the next generation of Physical AI for the real world.
About the team:
At Mentee Robotics, we are redefining humanoid automation with an AI-first approach - combining perception, reasoning, and dexterous manipulation into fully autonomous systems that continuously learn and adapt. We are now expanding with a new robotics Engineering Center in China, working hand-in-hand with our engineering teams in headquarters. Its mission: to rapidly develop our next-generation full-size humanoid and bring it to life - a walking, working platform that becomes the foundation of our next generation of products. This is a small, senior, hands-on team where speed of iteration is the core value. We are looking for a Motion Control Engineer to own the control algorithms of every joint in our humanoid - jointly with the embedded team, who implement your designs on the Motor Controller PCB. This is pure actuator control: FOC, loop design, estimation, and compensation. Whole-body behavior lives in learned policies; your job is to make every joint execute its commands perfectly.
Who you are
- A motor control specialist who can take a noisy, nonlinear physical joint and make it track like a servo catalog page
- Equally fluent in control theory and in what the silicon can actually compute in a 60 kHz loop
- Data-driven: you tune with measurements, plots, and system identification - not by feel alone
Responsibilities
- Define and validate the motor control methodology across the robot: FOC and commutation strategies for BLDC motors in quasi-direct-drive configurations with planetary reduction
- Design current, velocity, and position/torque control loops; define bandwidths, filtering, anti-windup, and saturation handling
- Develop torque estimation, friction and cogging compensation, and observers for joint state
- Define joint-level safety limits and fault-handling behavior together with embedded
- Guide and verify the embedded implementation of your algorithms on the Motor Controller PCB; co-own everything running on that board
- Design and execute structured characterization tests on the joint dyno: torque, speed, resolution, responsiveness, thermal behavior
- Deliver validated actuator models and control limitations to the Sim2Real and RL teams - your measured envelopes become their training constraints
- Drive improvements in actuation repeatability and responsiveness through precise measurement and feedback
Requirements
- B.Sc. or M.Sc. in Electrical, Mechanical, or Control Engineering (or equivalent experience)
- 8+ years in motor control systems or motion system integration
- Deep hands-on experience with FOC and current/velocity/position loop design for BLDC motors
- Familiarity with planetary gear systems and QDD architectures, and their impact on control and sensing
- Proven ability to define and lead performance test plans from lab setup to interpretation
- Comfortable using lab tools (oscilloscopes, encoders, current sensors) to evaluate dynamic behavior under load and in closed loop
- Impedance control and proprioceptive actuation experience
Advantages
- Experience in robotic or humanoid actuation or servo drive companies
- Familiarity with harmonic gear systems and their control implications
- Python for scripting, system identification, and data analysis
- Understanding of how sensor noise, latency, and actuation limits affect learned whole-body policies
- Comfortable communicating technical topics in English with international teams


