Senior Reinforcement Learning Engineer - Robotics

About the role

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.

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.

Requirements

• Advanced degree in Mechanical Engineering, Computer Science, Robotics, or a related field. Open to fresh graduates.
• 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.
• Proven experience applying algorithms such as PPO, DQN, SAC, etc., to real-world problems.
• Experience with C++ is a plus.
• Hands-on experience with the control and operation of legged robot hardware is highly preferred.

Benefits

• A fun, supportive and engaging environment.
• Opportunities to make a significant impact on the future of transportation and robotics.
• Opportunity to work on cutting edge technologies with the top talent in the field.
• Competitive compensation package & benefits.
• Snacks, lunches, and fun activities.
• Bonus, equity, and benefits.

Pay

The base salary range for this full-time position is $174,720 - $295,680, in addition to bonus, equity and benefits. Salary ranges are determined by role, level, and location; the range displayed reflects the minimum and maximum target for new hire salaries across all US locations. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.