Reality Labs Research (RL-R) is looking to advance 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.
Requirements
- 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
- 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)
Responsibilities
- 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
Other
- 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.
- collaborate across an interdisciplinary team
- 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 working and communicating cross-functionally to collaborate across disciplines and organizations
