Job Description
- 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
Key skill Required
- Algorithm
- Algorithms
- Analysis
- Autonomy
- C++
- Computer Science
- Data Analysis
- Decision Tree
- Deep Learning
- Design
- Experience Design
- Learning
- Machine Learning
- Optimization
- Publications
- Reinforcement
- Reinforcement Learning
- Research
- Robotics
- Science
- TensorFlow
- Trajectory Optimization
