Research Scientist Intern

About the Role

Meta Reality Labs brings together researchers and engineers to invent the future of visual computing. Our teams develop technologies that enable people to capture, create, understand, and interact with immersive visual experiences across Meta’s products and AR/VR platforms. We work at the intersection of artificial intelligence, computer vision, computer graphics, and computational photography. Our research spans generative image and video models, multimodal foundation models, neural rendering, novel-view synthesis, and learned 3D and 4D representations of people, objects, and environments.

As a Research Scientist Intern, you will help advance the state of the art through an ambitious research project. You will collaborate with researchers and engineers to develop new models, representations, datasets, and evaluation methods—with opportunities to publish your work and influence future products used by people around the world.

Key Responsibilities

• Research, develop, and prototype advanced technologies in the domain of 3D/4D reconstruction/rendering, image and video diffusion, world models, Gaussian splatting, neural fields, or diffusion transformers.
• Analyze the efficiency, accuracy, scalability, and stability of currently deployed technologies to identify opportunities for impact through novel research.
• Collaborate with team members throughout the lifetime of a project, from research to prototyping to deploying products.

Requirements & Tech Stack

• Experience in one or more areas of Computer Science, such as Computer Vision, Computer Graphics, Image Processing, and Computational Photography, more specifically: 3D/4D reconstruction/rendering, image and video diffusion, world models, Gaussian splatting, neural fields, or diffusion transformers.
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as co-authored publications at top-tier conferences.
• Experience with modern C++ and/or Python.
• Experience with deep learning frameworks such as PyTorch.

Qualifications

• Ph.D. student in a relevant field.
• Intent to return to their degree program after the completion of the internship.
• Interpersonal experience: cross-group and cross-culture collaboration.
• Strong communication skills and ability to convey research ideas to a broad audience.
• Broad understanding of the full machine vision pipeline from sensors to high-level algorithms.
• Mathematical background and understanding of linear algebra, numerical optimization, probabilistic estimation.
• Understanding of 3D geometry.
• Relevant research or software engineering work experiences, including internship, work experience, coding competitions, or widely used contributions in open source repositories.