Research Scientist Intern, Generative AI (PhD)

Our Maps Research team explores, develops, and delivers novel and cutting-edge technologies for photorealistic 3D scene reconstruction and generation, serving as the foundation for future AR/VR products. Our team is addressing a variety of technical challenges in the areas of consistent 3D generation, reconstruction refinement, and large-scale training. We're looking for candidates who share a passion for exploring and solving complex, challenging problems of 3D generative modeling.

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 3D content), as well as an outstanding software engineer who can prototype invented algorithms.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Responsibilities:

• Actively driving and participating in cutting edge research for 3D scene synthesis
• Developing efficient deep neural network models for 2D/3D/video content generation
• Contributing research that can be applied to Meta VR/AR product development
• Together with our team, work towards a top-tier, scientific publication

Minimum Qualifications:

• Hands-on knowledge with generative models (diffusion models, GANs) for image, object, scene, or video generation, etc
• 2+ years experience with PyTorch and Python
• 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
• 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

Preferred Qualifications:

• 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 models, GANs), 3D representations (NeRFs, 3D Gaussian Splatting), 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)