Hybrid Staff Reinforcement Learning Engineer - Robotics na Xpeng motors
Xpeng motors · Santa Clara, CA, Estados Unidos Da América · Hybrid
- Escritório em Santa Clara, CA
Job Responsibilities:
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Research, implement, and evaluate deep-learning-based methods for legged locomotion and whole-body control problems in humanoid robots.
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Develop and refine end-to-end robot motion controllers using reinforcement learning, imitation learning, or other advanced techniques.
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Design, execute, and analyze experiments to evaluate RL controllers and address sim-to-real challenges.
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Stay updated and integrate the latest advancements in academic and engineering research for humanoid robotics.
Minimum Requirements:
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Advanced degree in Mechanical Engineering, Computer Science, Robotics, or a related field.
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Proficiency in Python and strong software design skills.
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3-5+ years of experience with deep learning frameworks like PyTorch.
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Strong understanding of reinforcement learning and imitation learning techniques.
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Proven experience applying algorithms such as PPO, DQN, SAC, etc., to real-world problems.
Preferred Requirements:
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Experience with C++ is a plus.
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Hands-on experience with the control and operation of legged robot hardware is highly preferred.
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A fun, supportive and engaging environment
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Opportunities to make a significant impact on the future of transportation and robotics.
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Opportunity to work on cutting edge technologies with the top talent in the field
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Competitive compensation package & benefits
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Snacks, lunches, and fun activities