Key Responsibilities

• Develop and implement model-based controllers (e.g., PID, whole-body control, MPC) for humanoid locomotion and manipulation.
• Design dynamic balance, gait generation, and disturbance recovery algorithms using analytical and optimization-based methods.
• Work with estimation engineers to fuse sensor data (IMU, joint encoders, force/torque sensors, vision) for state estimation and feedback control.
• Perform system identification and develop accurate dynamic models for control and simulation fidelity.
• Conduct experiments to evaluate control robustness, energy efficiency, and locomotion performance metrics.

Requirements

• Bachelor or higher in Mechanical Engineering, Robotics, Control Systems, or related field.
• Strong background in robot dynamics and control theory, including rigid-body dynamics, optimal control, and nonlinear systems.
• Proficiency in C++ and Python for real-time control and simulation.
• Hands-on experience with model-based controllers such as MPC, WBC, or impedance control.
• Familiarity with ROS / ROS 2, Eigen, and real-time middleware.
• Experience with dynamic simulation tools (e.g., Gazebo, PyBullet, MuJoCo, Drake, RaiSim).

Compensation:

– VinDynamics offers a competitive base, full benefits and other incentives. Flexible time-off policy. Focus on output and ability to work with an interdisciplinary team.

Location: Hanoi, Vietnam.