Senior Robotics Software Engineer (Locomotion)

ABOUT VINDYNAMICS:

At VinDynamics, we design safe, affordable, and intelligent humanoid robots to assist in everyday life — robots for everyone. Backed by Vingroup, Vietnam’s leading technology conglomerate, we are on a mission to make advanced robotics accessible, reliable, and beneficial for billions of people worldwide. By combining cutting-edge AI, world-class engineering, and human-centered design, we aim to seamlessly integrate robots into daily life — enhancing safety, productivity, and happiness at home and beyond.

I. OVERVIE

• WPosition: Senior Reinforcement Learning Engineer (Humanoid Robot
• )Division - Department: R&D Divisio
• nReport to: Head of Mobilit
• yLocation: Reno, Nevad

a
II. REQUIREMEN

TSRelevant education and experien

• ceM.S. or Ph.D. in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related fie
• ldSolid understanding and experience of RL algorithms (PPO, SAC, TD3, A3C, etc.) and policy optimizati
• onHands-on experience with simulation platforms such as Isaac Gym/Isaac Lab, MuJoCo, PyBullet, or Gazeb
• o.Experience integrating learned policies with real robots (e.g., quadrupeds, manipulators, or mobile arm

s)Preferred Qualificatio

• nsExperience with locomotion, motion control, or physical control systems (e.g., legged robots, drones, exoskeletons, robotic arms
• ).Experience in sim-to-real transfer, domain randomization, or system identification in robotic
• s.Proficiency in Python and/or C , and familiarity with ML frameworks such as PyTorch, TensorFlow, or JA
• X.Strong analytical and debugging skills for physical systems; ability to identify stability and performance bottleneck
• s.Familiarity with sensor fusion, feedback control, and proprioceptive sensin

g.Personality/ Attitu

• deStrong interpersonal, organizational and leadership skil
• lsProactive, dedicated, business-oriented, responsible and willing to lea
• rnGood communication skills, creative problem-solving skills and attention to detai

l.
III. JOB DESCRIPT

• IONDevelop and implement reinforcement learning algorithms specialized for locomotion tasks (e.g., walking, running, climbing, balancing) and loco-manipulation tasks (e.g., walking while carrying or manipulating object
• s).Design, integrate, and optimize high-fidelity simulation environments for safe and efficient policy traini
• ng.Conduct sim-to-real transfer by addressing robustness, domain randomization, and system identification challeng
• es.Incorporate perception, sensor feedback, and proprioception into RL agents to enable adaptive and reactive moti
• on.Evaluate and benchmark locomotion policies under diverse real-world conditions (e.g., terrain variation, disturbances, slopes, payloads, and frictio
• n).Work on reward design, stability, sample efficiency, and safety-constrained learni
• ng.Write clean, maintainable, and well-documented code, ensuring reproducibility and version control for experiments and polici