2 months ago
Base Salary
$175k - $296k/yr
Responsibilities
- Research, implement, and evaluate deep-learning methods for legged locomotion and whole-body control 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 for reinforcement-learning controllers and sim-to-real challenges.
- Track and integrate advances from academic and engineering research in humanoid robotics.
Requirements
- Advanced degree in Mechanical Engineering, Computer Science, Robotics, or a related field; fresh graduates are welcome.
- Proficiency in Python and strong software design skills.
- At least 1 year of experience with deep-learning frameworks such as PyTorch.
- Strong understanding of reinforcement learning and imitation learning techniques.
- Demonstrated experience applying PPO, DQN, SAC, or similar algorithms to real-world problems.
- C++ experience is preferred.
- Hands-on experience controlling and operating legged-robot hardware is highly preferred.
Benefits
- Competitive compensation package and benefits, plus snacks, lunches, and fun activities.
- Supportive and engaging work environment with opportunities to impact transportation and robotics.
- Opportunity to work with cutting-edge technologies and leading talent in the field.
Categories
ML EngineeringRobotics
About XPENG
XPENG designs, manufactures, and sells smart electric vehicles for consumers, integrating in-house advanced driver-assistance systems and connected in-car software. Founded in 2014 and headquartered in Guangzhou, it operates plants in Zhaoqing and Guangzhou, maintains a European HQ in Amsterdam, and develops eVTOL aircraft via XPENG AEROHT.