Senior Reinforcement Learning Engineer - Robotics

Job 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.
  
  

Minimum 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.
  
  

Preferred Requirements:

• Experience with C++ is a plus.
  
  
• Hands-on experience with the control and operation of legged robot hardware is highly preferred.
  
  

• 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.