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.
This role offers the chance to have broad impact on the next wave of robotics You will collaborate with brilliant colleagues in a culture that values ingenuity, teamwork and delivering impact. Come join our mission to pioneer the future of automation!
About the team
Our multi-disciplinary science team includes scientists with backgrounds in simulation, planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including:
* 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
Our team also serves as a hub to foster innovation and support scientists across Amazon Robotics. We also coordinate research engagements with academia, such as the Robotics section of the Amazon Research Awards.
BASIC QUALIFICATIONS
* 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
PREFERRED QUALIFICATIONS
* Extensive experience developing and deploying algorithms for planning and control of real world applications
* Deep knowledge of adjacent fields, including 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
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.