Job Description
On the Motion Planning team at Zoox, you’ll be dedicated to improving the driving behaviors of the robot on public roads. The Planner's job is to figure out where the robot is going and how to get there safely in situations as complex as those found in Downtown San Francisco or on the Las Vegas Strip.
This is a cutting-edge problem, which requires teamwork and collaboration across a broad set of experts spanning Planner, Perception, Prediction, Operations, and more. Together, you will create the next generation of algorithmic improvements to expand our robot’s ability to drive in some of the most complex situations found on public roads.
Safety is foundational at Zoox, so you will take a measured approach – develop a principled modification to the Planner, test in simulation and on closed courses, and team up with our safety drivers for on-road testing.
Qualifications
- Master's degree in Computer Science or related field and 8+ years of experience
- Fluency in C++
- Understanding of configuration spaces and a variety of planning techniques (A*, RRTs, PRMs, etc.)
- Demonstrated ability to create real-time motion planning algorithms
Bonus Qualifications
- Significant contributions to geometric- and/or sampling-based planning algorithms
- Experience with autonomous robots and machine learning or data-driven development processes
- Experience with ROS, pose estimation, SLAM, probabilistic filtering, 3D data, or CUDA
Requirements
Qualifications
- Master's degree in Computer Science or related field and 8+ years of experience
- Fluency in C++
- Understanding of configuration spaces and a variety of planning techniques (A*, RRTs, PRMs, etc.)
- Demonstrated ability to create real-time motion planning algorithms
Bonus Qualifications
- Significant contributions to geometric- and/or sampling-based planning algorithms
- Experience with autonomous robots and machine learning or data-driven development processes
- Experience with ROS, pose estimation, SLAM, probabilistic filtering, 3D data, or CUDA
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