At Reality Labs Research, our goal is to explore, innovate and design novel interfaces and hardware for the next generation of virtual, augmented, and mixed reality experiences. We are driving research towards a vision of natural, seamless experiences in XR environments that are effective, enjoyable, and functionally indistinguishable from those in the real world. As a Research Scientist Intern, you will work at the intersection of robotic control, machine learning, and human-robot interaction, and you will have the opportunity to work with world-leading collaborators and mentors in these fields. Your primary focus will be on developing data-driven/ML-powered robotic control policies for dextrous manipulation and teleoperation applications. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Responsibilities
Conduct collaborative research on developing control policies for a range of robotics platforms. Implement frameworks to train state-of-the-art machine learning control policies such as Large Behavioral Models, Imitation Learning, and Reinforcement Learning. Develop robotic data collection pipelines for robotic dextrous manipulation, train models, and benchmark different algorithms. Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Qualifications
Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Robotics, or relevant technical field Understand state of the art in robotic manipulation control policies, and advancing the technological frontier in an impactful and efficient way Experience with RoS, Python, PyTorch or JAX, or other related languages Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Experience with modern control policies like reinforcement learning, imitation learning, and large behavioral models Familiarity with modeling and analysis used in robotics including kinematics, dynamics, motion planning, perception, task planning, and control theory Experience working with robot manipulation Experience learning policies from human demonstrations with wearable devices Experience working and communicating cross functionally in a team environment Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as Robotics (RSS, ICRA, IROS, CoRL, T-RO, IJRR), Machine Learning (NeurIPS, ICML, ICLR, AAAI, JMLR), and Computer Vision (CVPR, ICCV, ECCV, TPAMI), or similar Intent to return to the degree program after the completion of the internship/co-op