Amazon Principal Applied Scientist - Planning Learning Amazon Robotics 

United States, Massachusetts 

17198854

In this position, you will own the science of planning and scheduling fleet activities to achieve system-level objectives across a broad range of building types and workflows. You will improve the algorithms that control today’s global robotic fleet to unlock new opportunities for Amazon’s evolving network, as well as develop new capabilities from the ground up. You will explore how to leverage the power of our robotic mobility foundation model to predict the motion of the fleet to enable new ways of making decisions at scale. You will influence the design of future warehouses and the integration of new robotic technologies.* Planning and coordinating the paths of thousands of robots
* Dynamic allocation and scheduling of tasks to thousands of robots
* Learning how to adapt system behavior to varying operating conditions
* Co-design of robotic logistics processes and the algorithms to optimize them

* PhD degree in Robotics, CS or related technical field
* 10+ years of relevant, broad research experience after a PhD degree
* Experience programming in C++, Java, Python or related language
* Experience using state of the art planning and machine learning methods
* Strong publication record with contributions to leading conferences/journals

* Extensive experience developing and deploying algorithms for planning and control of real world applications
* Deep knowledge of adjacent fields, including optimization, heuristic search, and deep learning
* Comfort working in a fast-paced development environment
* Ability to identify unsolved problems and creatively invent solutions
* Proven track record of innovation