Humanoid Robotics

We’re Hiring: Principal Robotics Controls Engineer – Locomotion & MPC/RL

📍 Location: Singapore

🏢 Work Mode: Remote

💼 Experience: 8+ Years

🎓 Qualification: Master’s or Ph.D. in Robotics, Mechanical Engineering, or Mechatronics

About the Role

We are looking for an experienced Principal Robotics Controls Engineer to lead the development of advanced locomotion, dynamic balance, and real-time motion control systems for legged robots.

In this role, you will design and optimize control architectures that bridge high-level Vision-Language-Action (VLA) directives with low-level motor control, enabling robots to navigate complex terrain, recover from disturbances, and perform dynamic movements reliably.

Key Responsibilities

Lead the end-to-end locomotion stack, integrating high-level VLA commands with deterministic, real-time motor controllers.

Design and implement Nonlinear Model Predictive Control (NMPC), Whole-Body Control (WBC), and Deep Reinforcement Learning (RL) locomotion policies.

Validate robotic gait transitions, obstacle negotiation, push recovery, and stair traversal on physical hardware.

Develop large-scale Sim-to-Real training pipelines using NVIDIA Isaac Lab/Isaac Gym or RaiSim.

Implement high-frequency state estimation, contact detection, and slip-recovery algorithms.

Integrate high-speed motor communication systems using CAN-FD and EtherCAT.

Drive improvements in locomotion stability, terrain adaptability, control performance, and system reliability.

Required Qualifications & Technical Expertise

Master’s or Ph.D. in Mechanical Engineering, Robotics, Mechatronics, or a related field.

8+ years of hands-on experience in dynamic legged locomotion, multibody kinematics, and real-time control systems.

Strong expertise in modern C++, preferably C++20, and robotics frameworks such as Pinocchio, Drake, and OCS2.

Experience with Nonlinear MPC, Whole-Body Control, Quadratic Programming (QP), and robot kinematics and dynamics.

Hands-on experience with NVIDIA Isaac Gym/Isaac Lab, RaiSim, or equivalent robotics simulation platforms.

Strong understanding of PREEMPT_RT Linux and high-frequency control architectures.

Experience with real-time motor communication protocols, including CAN-FD and EtherCAT.

Preferred Background

Experience developing advanced legged robotics systems at organizations such as Boston Dynamics, Ghost Robotics, or Rainbow Robotics, or research experience with leading robotics laboratories such as Carnegie Mellon University’s Robomechanics Lab or MIT’s Biomimetic Robotics Lab, would be highly relevant.