The Motion Planning team specialized in Machine Learning, researches new deep learning approaches, builds deep neural networks, algorithms, and software to impact across navigation, behavior, route planning, as well as trajectory optimization, numerical optimization, and model predictive control. The team is experimental and once an idea is effective, works to put into production.
Motional's Machine Learning team has produced ground breaking advancements in the autonomous vehicle industry including nuScenes (https://www.nuscenes.org), PointPillars (https://arxiv.org/abs/1812.05784), and PointPainting (http://arxiv.org/abs/1911.10150)
- Prototype our next generation motion planning systems being the intersection between prediction, motion planning and controls
- Initiate and collaborate on new research projects to further extend the domain of autonomous driving capabilities
- Publish results at conferences
- Masters, or PhD in Robotics, Computer Science, Applied Mathematics, Statistics or a related field with at least 1 year hands-on experience
- Experience designing, training, analyzing, and deploying neural networks for at least one of the following applications: Motion Planning, Motion prediction, Behavioral prediction.
- Experience in Machine Learning and Motion planning
- Fluency in Python and/or C++
- Experience with PyTorch or other deep learning frameworks
- Proven track records in patent and/or publications
- Ability to comfortably explore uncharted territories
- Knowledge of software engineering principles, including software design, source control management, build processes, code reviews, and testing methods
- Experience as a self-directed engineer / research scientist who excels at driving new research ideas from conception and experimentation to productization
- Experience in Model Predictive Control, vehicle dynamics, and simulation environments
- Experience in Game Theory