Research Intern - Computational Imaging

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.

Snap Research serves as an innovation engine for the company. Our projects range from solutions to hard technical problems that significantly enhance Snap’s existing products, to riskier explorations that can lead to fundamental paradigm shifts in the way people communicate and express themselves. The team consists of scientists and engineers who experiment with and invent new technology that has a lasting impact on Snap’s products. We also frequently publish our work at top conferences and journals in computer science and related fields.

We are looking for Research interns to join our Computational Imaging Research Team! The Computational Imaging team in NYC focuses on enhancing user experiences with our photo and short form video products, and enabling our creators to make Lenses more easily in Lens Studio. Specifically, our core focus in 2026 is on improving image and video quality (quality assessment, video super resolution, compression, image editing), and animations (animation generation, 3D avatar, video generation for animations). Our research areas include computer vision, computational imaging/photography, 3d motion/video generation, efficient VLMs, and more.

What you'll do:

• Lead research in computer vision across low-level vision, efficient VLMs, and avatar/animation/video generation

• Build research prototypes and evaluate them in real application scenarios

• Publish your findings at top conferences

Knowledge, Skills, & Abilities:

• Strong technical knowledge of state-of-the-art DL algorithms in one or more above sub-areas 

• Demonstrated ability in defining, leading and executing challenging research projects

• Strong computer science fundamentals, problem-solving and engineering skills
   

Minimum Qualifications:

• Track record of (co-)first-author publications in top venues, e.g. CVPR, NeurIPS, Siggraph

• Currently enrolled in a PhD (or MS) program in a technical field such as computer science, computer engineering, machine learning, statistics, mathematics

• Strong foundation in computer vision, 3D graphics, and multimodal learning

• Strong theoretical foundations of generative AI and practical experience training, tuning, and modifying generative models

• Hands-on experience with state-of-the-art neural network techniques such as CNNs, Transformers, GANs, diffusion models, VAEs, and/or other emerging techniques

Preferred Qualifications:

• Hands-on experience in large scale dataset curation and distributed ML model training such as image/video/audio generation model pre-training or post-training

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