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Meta · 2 months ago

Research Scientist Intern, Computer Vision - Video Intelligence (PhD)

Menlo Park, CA

Internship

Onsite

Intern

$7,650/mo - $12,134/mo

Meta is a technology company that builds tools to connect people and foster community. The Video Intelligence team is seeking highly motivated Research Interns to advance video generation technologies, working on innovative AI-driven video creation experiences and enhancing video content comprehension.

Computer Software

Comp. & Benefits

Responsibilities

Conduct research on advanced topics in video generation and understanding, including but not limited to text-to-video generative models, image-to-video generative models, video understanding models, unified native video generative models

Design, implement, and evaluate novel algorithms and model architectures

Collaborate closely with researchers and engineers across the Video Intelligence group and broader GenAI teams

Contribute to publications in top-tier conferences and journals in AI, computer vision, and machine learning

Present findings and share insights that help shape both ongoing research and future directions

Qualification

Ph.D. in Computer SciencePythonDeep learning frameworksGenerative modelsResearch experienceCross-functional communicationOpen-source contributions

Required

Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Electrical Engineering, or related field with a focus on generative modeling, computer vision, or machine learning

Programming experience in Python and hands-on experience in deep learning frameworks such as PyTorch

Experience working on generative models e.g. diffusion models, LLM, autoregressive transformers, etc

Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred

Intent to return to the degree program after the completion of the internship/co-op

Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, or SIGGRAPH

Strong track record of contributions to open-source projects, benchmarks, or shared research artifacts

Research experience in video generation, temporal modeling, multimodal learning or unified native video generative models

Experience working and communicating cross functionally in a fast-paced team environment. Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results