+ 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 + Publications in top conferences/journals in a related field or equivalent experiences is a plus