Teams at General Robotics

Develop and deploy reinforcement learning and imitation learning policies for whole-body humanoid locomotion and manipulation. Build high-fidelity simulation environments, improve sim-to-real transfer, conduct experiments, evaluate models, write reusable code, contribute to publications, and deliver policies to production customer sites. The role spans robotics research, computer vision, model development, and end-to-end deployment.

Design and build software and hardware for robotic teleoperation and large-scale data collection. Develop electromechanical devices, operator interfaces, backend processing, data-quality metrics, augmentation pipelines, and adaptation systems for robot learning. Work across robot arms and mobile manipulators, modern sensing hardware, robotics middleware, and manipulation policies. Collaborate with teleoperators, research teams, and customers to move robotic capabilities from prototypes into deployed products.

Develop production-grade robotic manipulation systems spanning foundation models, reinforcement learning, simulation, synthetic data, and real hardware. Train, adapt, evaluate, and deploy vision-language-action and related policies across robotic arms, mobile manipulators, and humanoids. Build scalable data and software pipelines, conduct end-to-end experiments, contribute to research publications and open source, and collaborate with customers to deploy manipulation capabilities.