Research Scientist Intern, Generative AI (PhD) (multiple locations)

We are looking for an exceptional PhD student with a proven track record in developing generative approaches for solving computer vision and graphics problems (e.g., conditional, generative models for videos or (dynamic) 3D content), as well as an outstanding software engineer who can efficiently prototype new ideas as well as integrate them into our large-scale data and training infrastructure.

Responsibilities

Actively driving and participating in cutting edge research for 3D/4D scene reconstruction, understanding & generation. Developing efficient deep neural network model architectures. Contributing research that can be applied to Meta wearables and AI development. Together with our team, work towards a top-tier, scientific publication.

Qualifications

Currently has, or is in the process of obtaining a PhD in the field of computer vision, computer graphics, machine learning, or a related field Hands-on knowledge with state-of-the-art model architectures (multi-view transformers, diffusion/autoregressive models, etc.,for image, object, scene, or video reconstruction, understanding, generation, etc.) Experience with PyTorch and Python Understanding of 3D geometry, statistical analysis of data, and mathematical modeling Excellent interpersonal and communication skills, cross-group and cross-culture collaboration High levels of creativity and quick problem solving capabilities Must obtain work authorization in the 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 conferences (e.g., SIGGRAPH, CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML) or journals (e.g., PAMI, IJCV, JMLR, ToG) Experience with generative models (e.g., diffusion/autoregressive models), multi-view transformers (e.g., VGGT, MapAnything), 3D/4D representations (point clouds, Gaussian Splatting), video generation (e.g. WAN/Cosmos), and inverse rendering techniques Experience in 3D computer vision, graphics, and deep learning models for this domain Demonstrated software engineer experience via previous internships, work experiences, coding competitions, or widely used contributions in open source repositories (e.g. GitHub) Familiarity with AI native coding practices workflows