At Reality Labs Research (RL-R), our goal is to explore, innovate and design novel interfaces and hardware subsystems for the next generation of virtual, augmented, and mixed reality experiences.We are looking for a Research Scientist with expertise in multimodal ML and CV and experience in robotics applications to join our team within Reality Labs Research. You will work on advancing the state of the art for hand-centric foundation models for dexterous manipulation by leveraging groundbreaking advances in tools for human and robot data collection. You will work with a broad and highly interdisciplinary team of researchers, engineers, and designers, and will have access to cutting edge technology, resources, and testing facilities.

MINIMUM QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Ph.D. in Artificial Intelligence, Robotics, Computer science, relevant technical field, or equivalent practical experience
• 5+ years experience in advanced ML techniques such as representation learning, self-supervised learning, cross-embodiment, multimodal learning, vision-language-action (VLA) models, reinforcement learning, imitation learning, LLMs, and/or robotics policy development
• 5+ years experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and programming in Python
• 2+ years experience in robotics-related research areas
• Experience manipulating and analyzing complex, large scale, high-dimensionality multimodal data from varying sources

PREFERRED QUALIFICATIONS:

• A track record of research output with work published in top conferences and journals such as Robotics (RSS, ICRA, IROS, CoRL, T-RO, IJRR), Machine Learning (NeurIPS, ICML, ICLR, AAAI, JMLR), and Computer Vision (CVPR, ICCV, ECCV, TPAMI)
• Experience designing data collection protocols and constructing high quality machine learning datasets
• Experience bringing-up and debugging prototype/scientific software-hardware systems (e.g., robotics platforms, multi-camera sensing/tracking solutions, wearable sensing systems)
• Experience working and communicating cross-functionally to collaborate across disciplines and organizations

• Develop machine learning and computer vision models for applications such as robotics, dexterous manipulation, hand pose estimation, object detection, contextual understanding, and gesture recognition
• Design and implement ML pipelines and systems that collect and process datasets and enable algorithm experimentation
• Develop experimental protocols for human-subjects research and collaborate across an interdisciplinary team to collect multimodal datasets from prototype wearable sensing systems