Research Scientist Intern, FAIR - Video Generation (PhD)
About The Position
Meta is seeking a Research Intern to join the Fundamental AI Research (FAIR) Communication & Language team within Meta Superintelligence Labs (MSL). The team aims to advance the science of intelligence and develop technologies that push the boundaries of AI. The intern will focus on video generation and post-training large-scale models, contributing to perceptual and generative foundations for next-generation AI systems. The role offers collaboration with interdisciplinary scientists, engineers, and cross-functional partners, as well as access to cutting-edge technology, research resources, and facilities. Interns may make core algorithmic advances and apply their ideas at scale. The work may cover generative modeling for video, including diffusion, flow matching, and video synthesis; post-training large-scale video and multimodal models through SFT/RL, optimization, and data curation; video-language models and architectures for video generation; multimodal understanding, reasoning, and generation; frontier model development such as Llama and LMMs; and perceptual foundations for real-time embodied agents and conversational AI. Internships last 12 to 24 weeks, with various start dates throughout the year.
Requirements
- Currently have or be in the process of obtaining a PhD in Computer Science, Electrical Engineering, Computer Vision, Machine Learning, Artificial Intelligence, a relevant technical field, or equivalent.
- Research and/or work experience in video generation, computer vision, or multimodal AI.
- Experience with large-scale model training, post-training optimization techniques, and/or data curation.
- Experience with Python, C++, or other related languages, and deep learning frameworks such as PyTorch or TensorFlow.
- Must obtain work authorization in the country of employment by the time of hire and maintain ongoing work authorization during employment.
Nice To Haves
- Demonstrated research and software engineering experience through internships, industry or academic work, coding competitions, or widely used open-source contributions.
- Experience with video generation, video synthesis, or multimodal fusion techniques.
- Experience with video-language models and architectures relevant to video generation and post-training.
- A record of significant results demonstrated through grants, fellowships, patents, or publications at leading workshops, journals, or conferences such as NeurIPS, ICML, ICLR, CVPR, or ICCV.
- Experience manipulating and analyzing complex, large-scale, high-dimensional data from varying sources.
- Experience solving complex problems and evaluating alternative solutions, tradeoffs, and perspectives to determine a path forward.
- Experience working and communicating cross-functionally in a collaborative, interdisciplinary team environment.
- Intent to return to the degree program after completing the internship/co-op.
Responsibilities
- Conduct fundamental and applied research in video generation, including generative models, video synthesis, and multimodal learning.
- Develop and optimize post-training paradigms for large-scale video and multimodal models to improve performance, robustness, and generalization.
- Collaborate with teams across Meta to build perceptual foundations for real-time embodied agents and conversational AI.
- Contribute to frontier model development, including models such as Llama and LMMs, and advance video and media generation.
- Brainstorm with research mentors and review literature and existing solutions to challenging real-world research problems.
- Develop novel solutions, implement prototypes, and conduct experiments using meaningful benchmarks and metrics; analyze results and verify conclusions.
- Draft and polish research reports and/or publications.
- Present research outcomes to internal and/or external audiences.
- Contribute research that can be applied to Meta product development.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
