Machine Learning Engineer, Planning, Prediction and Control in California

• Develop Learning based planning algorithms for trajectories (deep learning, reinforcement learning, decision trees, etc) to ensuring that the vehicle behavior is natural, safe and smooth
• Design policies and plans to manage multi-actor interactions and plans under uncertainty
• Work with other internal autonomy teams to help to continuously improve and refine the self-driving system

Requirements

• Master or Ph.D. degree in Computer Science, Electric Engineering or a related field
• Experience solving problems using Machine Learning with Tensorflow or equivalent tools
• Professional C++ experience designing any-angle robotic navigation algorithms such as Dijkstra, A*, D*, RRT, RRT* and RRG
• Experience in at least one of: robotics research in motion planning, trajectory optimization, planning under uncertainty, probabilistic robotics, data analysis at scale, machine learning at scale
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