Senior/Staff Machine Learning Engineer (Reinforcement Learning, Motion Planning)

• Design, develop, and deploy learned behavior planning models using approaches such as reinforcement learning, behavior cloning, and imitation learning
• Own end-to-end Reinforcement Learning pipeline from environment construction, training, and modeling
• Contribute to Reinforcement Learning Infrastructure to facilitate large-scale distributed training
• Track model training, analyze model performance, identify failure modes to improve generalization across driving scenarios
• Collaborate with simulation and planning teams to deploy learned behavior planning models to driving pipelines

Benefits

• Unlimited PTO: Unlimited paid time off on top of company holidays to recharge and enjoy as needed
• Flexible working: Flexibile work arrangements and technology to help manage life’s demands at the office and remote
• Health benefits: Tiered options in medical, dental, and vision insurance to fit your unique needs
• Future building: Equity, 401k and FSA options for all eligible employees to help build for your future
• Professional development: Company-sponsored professional development opportunities such as conferences, training, and workshops
• Catered lunches: Daily catered lunches at both of our Santa Clara and Fremont offices

Preferred experience

• MS or PhD in Computer/Software Engineering, Robotics, Machine Learning or related field
• Experience developing production code in C/C++ and Python
• Experience with machine learning frameworks such as PyTorch
• Strong oral and written communication skills
• Experience with reinforcement learning
• Experience with high-throughput batched driving simulators such as GPUDrive and PufferDrive
• Experience with sim-to-real in the context of robotics / autonomous driving
• Experience with self-play reinforcement learning
• Prior experience in learned behavior planning / prediction for autonomous vehicles