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Position Overview

We are seeking a Principal Robotics Controls Engineer (Locomotion & MPC/RL) to lead the development of locomotion, dynamic balance, and real-time motion control systems for advanced legged robots.

You will design and implement control algorithms that enable robots to navigate uneven terrain, transition between gaits, recover from external disturbances, and execute movements reliably. The role combines robotics dynamics, model predictive control, reinforcement learning, simulation, and real-world hardware validation.

Key Responsibilities

Lead the development of the locomotion and motion control stack for legged robots.
Translate high-level navigation goals into stable, executable robot movements.
Design and implement nonlinear Model Predictive Control (NMPC), Whole-Body Control (WBC) , and related optimization-based control methods.
Develop locomotion policies using deep reinforcement learning where appropriate.
Implement robot kinematics, dynamics, state estimation, contact detection, and slip-recovery algorithms.
Develop and validate gait transitions, obstacle negotiation, stair climbing, and recovery from external disturbances.
Build simulation-based training and testing pipelines using NVIDIA Isaac Lab, Isaac Gym, RaiSim , or comparable robotics simulation environments.
Develop Sim-to-Real workflows to transfer locomotion policies from simulation to physical robots.
Integrate motion control systems with motor controllers and communication networks, including CAN-FD and EtherCAT .
Optimize control performance for low-latency, deterministic execution on real-time Linux systems.
Collaborate with mechanical, embedded, perception, and AI teams to validate complete robotic systems.

Qualifications

Master's or Ph.D. in Mechanical Engineering, Robotics, Mechatronics, Electrical Engineering, or a related field.
At least 8 years of practical experience in robotics, motion control, legged locomotion, or closely related control engineering.
Strong understanding of robot kinematics, rigid-body dynamics, and multi-body systems.
Hands-on experience developing locomotion or motion control algorithms for legged robots.
Strong proficiency in modern C++ and C++20 .
Practical experience with Model Predictive Control (MPC), nonlinear optimization, and Quadratic Programming (QP).
Experience with Whole-Body Control (WBC) or related model-based control approaches.
Familiarity with robotics libraries and frameworks such as Pinocchio, Drake, or OCS2.
Experience with reinforcement learning for robotics or locomotion policy development.
Familiarity with NVIDIA Isaac Lab, Isaac Gym, RaiSim, or equivalent simulation platforms.
Understanding of real-time control and PREEMPT_RT Linux environments.
Experience integrating control software with physical robot hardware and motor communication systems.
Strong problem-solving skills and the ability to lead complex robotics engineering projects.

Why Join?

Lead the development of advanced robotic locomotion and control systems.
Work on challenging problems involving dynamic balance, terrain traversal, and autonomous movement.
Combine control theory, simulation, reinforcement learning, and physical robot testing.
Collaborate with cross-functional engineering teams to move robotics research into practical applications.

Principal Robotics Engineer (Motion Control)

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