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Humanoid Locomotion Engineer
Job in
Reno, Washoe County, Nevada, 89550, USA
Listed on 2026-07-01
Listing for:
VinDynamics
Full Time
position Listed on 2026-07-01
Job specializations:
-
Software Development
Robotics
Job Description & How to Apply Below
- Develop and implement reinforcement learning algorithms specialized for locomotion tasks (e.g., walking, running, climbing, balancing).
- 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.
- Solid background in Reinforcement Learning (Deep RL, Policy Gradient, Model‑based RL, Imitation Learning, etc.).
- Hands‑on experience with simulation platforms such as Mu Jo Co , PyBullet, Isaac Gym, or Gazebo.
- 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, Tensor Flow, 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.
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