Reality Labs Research is pioneering the next generation of AR/VR devices and intelligent systems. Our mission is to create the foundational technologies that enable contextual AI for AR glasses, VR headsets, and embodied agents. We are advancing the state of the art in 3D perception, multimodal scene understanding, and efficient on-device intelligence.
Requirements
- Research background in at least one of: 3D scene understanding, semantic mapping, SLAM, or neural representations, Multimodal learning (vision + language, vision + audio), Large-scale 3D reconstruction or scene graph generation
- Programming skills in Python and PyTorch (or equivalent deep learning frameworks)
- Hands-on experience with 3D datasets, rendering, or AR/VR sensors
- Experience with hybrid 3D representations (e.g., Gaussian Splatting, NeRFs, octree/voxel methods)
- Familiarity with open-vocabulary or foundation models (CLIP, Segment-Anything, LLMs for vision-language reasoning)
- Knowledge of real-time or efficient deployment techniques (quantization, distillation, adaptive inference)
- Ability to integrate research code into practical prototypes on edge devices (Jetson, AR/VR headsets)
Responsibilities
- Conduct research in 3D scene understanding, including but not limited to: Efficient and scalable 3D representation learning or reconstruction, Hierarchical / semantic scene graphs for large-scale environments, Open-vocabulary multimodal grounding (text, image, video, audio etc), Dynamic object tracking and temporal scene reasoning, and Edge-aware 3D scene understanding.
- Design and execute experiments on public datasets and/or internal data from AR/VR hardware.
- Collaborate with researchers, engineers, and interns across Reality Labs to advance the research frontier.
- Document findings and aim for submission to CVPR or equivalent top-tier conferences.
Other
- Currently pursuing a PhD in Computer Vision, Machine Learning, Robotics, or a related field
- Proven publication record in top-tier venues (CVPR, ICCV, ECCV, NeurIPS, ICLR, etc.)
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
- Intent to return to degree-program after the completion of the internship/co-op
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences
