Meta is seeking Research Scientists to join Meta Superintelligence Labs (MSL) organization to work on making significant advances in AI. We are seeking researchers with experience in vision models, 3D reconstruction and generation, and general AI to join the team to investigate how to build spatial and physically-aware AI that will be the foundation for a new paradigm in how we interact and use computers. You will work with a highly interdisciplinary team of scientists, engineers, and cross-functional partners with a broad range of experiences, perspectives, approaches, and backgrounds and access cutting-edge technology, resources, and research facilities.
Responsibilities
Build models that can estimate underlying 3D properties from 2D observations Conduct research and work with models in 3D reconstruction and generation Define, build and benchmark new capabilities needed for the next generation of AI Train and optimize state-of-the-art machine learning and neural network methodologies Work with and create large datasets, and contribute to data annotation engines
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Currently has or is in the process of obtaining a PhD in the field of Computer Vision, Language, Machine Learning, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta Research Experience in deep learning, computer vision, robotics, or AI infrastructure Experience with Python and PyTorch Experience developing software and executing complex experiments Experience communicating research for public audiences of peers Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Research experience with 3D reconstruction, 3D generation, and / or video processing and generation Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as CVPR, ICCV, ICCV, NeurIPS, SIGGRAPH, or similar Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub) Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward Experience working and communicating cross functionally in a team environment