Robotics Software Engineer

Job Description

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. OVERVIEW
Position: Robotics Software Engineer
Division - Department: R&D Division
Report to: Head of Mobility
Location: Reno, Nevada
II. REQUIREMENTS
Relevant education and experience
M.S. or Ph.D. in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field
Solid understanding and experience of RL algorithms (PPO, SAC, TD3, A3C, etc.) and policy optimization
Hands-on experience with simulation platforms such as Isaac Gym/Isaac Lab, MuJoCo, PyBullet, or Gazebo.
Experience integrating learned policies with real robots (e.g., quadrupeds, manipulators, or mobile arms)
Preferred Qualifications
Experience 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 robotics
Proficiency in Python and/or C++, and familiarity with ML frameworks such as PyTorch, TensorFlow, or JAX
Strong analytical and debugging skills for physical systems; ability to identify stability and performance bottlenecks.
Familiarity with sensor fusion, feedback control, and proprioceptive sensing
Personality/ Attitude
Strong interpersonal, organizational and leadership skills
Proactive, dedicated, business-oriented, responsible and willing to learn
Good communication skills, creative problem-solving skills and attention to details
III. JOB DESCRIPTION
Develop 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 objects)
Design, integrate, and optimize high-fidelity simulation environments for safe and efficient policy training.
Conduct sim-to-real transfer by addressing robustness, domain randomization, and system identification challenges.
Incorporate perception, sensor feedback, and proprioception into RL agents to enable adaptive and reactive motion.
Evaluate and benchmark locomotion policies under diverse real-world conditions (e.g., terrain variation, disturbances, slopes, payloads, and friction)
Work on reward design, stability, sample efficiency, and safety-constrained learning
Write clean, maintainable, and well-documented code, ensuring reproducibility and version control for experiments and policies