Senior RL Engineer - Humanoid Robotics (Equity)

Socket.dev; Santa Clara (CA); On-site; USD 174,720 - 295,680; Full time

Benefits offered by this job

Competitive compensation

Snacks & meals

Opportunity to work on cutting edge技hn

Job summary

XPENG in Santa Clara is seeking a researcher engineer to advance deep-learning methods for legged robots and to develop end-to-end motion controllers using reinforcement learning and imitation learning. You will design experiments, evaluate controllers, and address sim-to-real challenges.

The role requires advanced degree, Python proficiency, 1–3+ years in DL with PyTorch, and practical RL experience with PPO, DQN, SAC. Experience with C++ and robotics hardware is a plus.

Qualifications

• Advanced degree in Mechanical Engineering, Computer Science, Robotics, or a related field.
• Proficiency in Python and strong software design skills.
• 1–3+ years of experience with deep learning frameworks like PyTorch.
• Strong understanding of reinforcement learning and imitation learning techniques.
• Experience applying PPO, DQN, SAC to real-world problems.

Responsibilities

• Research, implement, and evaluate deep-learning-based methods for legged locomotion and whole-body control problems in humanoid robots.
• Develop and refine end-to-end robot motion controllers using reinforcement learning, imitation learning, or other advanced techniques.
• Design, execute, and analyze experiments to evaluate RL controllers and address sim-to-real challenges.
• Stay updated and integrate the latest advancements in academic and engineering research for humanoid robotics.

Skills

Python

PyTorch

Reinforcement learning

Imitation learning

C++

Education

Advanced degree in Mechanical Engineering, Computer Science, Robotics, or related field

Tools

ROS

C++

Job description

XPENG in Santa Clara is seeking a researcher engineer to advance deep-learning methods for legged robots and to develop end-to-end motion controllers using reinforcement learning and imitation learning. You will design experiments, evaluate controllers, and address sim-to-real challenges.

The role requires advanced degree, Python proficiency, 1–3+ years in DL with PyTorch, and practical RL experience with PPO, DQN, SAC. Experience with C++ and robotics hardware is a plus.