Develop, integrate, and deploy algorithms linking perception to autonomous robot actions, including manipulation, navigation, and human-robot interaction.
Invent and deploy innovative solutions at the intersection of machine learning, mobility, manipulation, human interaction, and simulation for performing useful, human-level tasks in human environments.
Invent novel ways to engineer and learn robust, real-world behaviors, including using optimization, planning, reactive control, self-supervision, active learning, learning from demonstration, simulation and transfer learning, and real-world adaptation.
Work embedded within the Robotics Mobile Manipulation team to develop and integrate solutions enabling robots to perform complex mobile manipulation tasks, navigate with and among people, and learn and adapt over time.
Develop, deploy, and validate systems in real-world environments, bootstrapping from simulation and leveraging large amounts of data.
Requirements
B.S. or M.S. in an engineering related field.
Experience with inventing and deploying innovative autonomous behaviors for robotic systems in real-world environments.
Experience in areas such as reactive control, trajectory optimization, coordinated whole-body control, dexterous manipulation, arm motion planning, grasp planning, navigation, and human interaction.
Experience in applying machine learning to robotics, including areas such as reinforcement, imitation, and transfer learning.
Strong software engineering skills, preferably in C++, and analysis and debugging of autonomous robotic systems.
A team player with strong communication skills and a willingness to learn from others.
Passionate about seeing robotics have a real-world, large-scale impact.