Research Engineer, Embodied Ai, Sunnyvale

Responsibilities
Conduct research and development focused on robot perception, control, task planning, and model training to transition intelligent agents from the digital world to the physical world.
Design, train, evaluate, and deploy learning-based visuomotor policies for mobile, bimanual, dexterous, and loco-manipulation.
Apply and extend techniques, including behavior cloning, reinforcement learning, and VLA reasoning.
Contribute to building the full pipeline, from data collection on real robots to model training, evaluation, and deployment.
Work closely with simulation and digital twin tools where useful, while prioritizing real-world performance and transfer.
Write high-quality, well-tested software that runs reliably on physical robots.
Requirements
Bachelor's or Master's degree in a highly technical field such as computer science, mechanical engineering, electrical engineering, robotics, or a related field.
Experience with robotics, control, reinforcement learning, or multimodal learning.
Experience with physical robots, simulation, teleoperation, or manipulation.
Passion for building autonomous robots that operate in the real world.
Proficiency in Python and/or C++ for robotics and machine learning systems.
Bonus Qualifications
Publication record in top robotics, computer vision, or machine learning conferences or journals.
Hands-on experience developing and deploying robot learning systems on real robots.
Deep understanding of compliance control, such as impedance or admittance control.