Research Scientist Intern, FAIR - Video Generation Self-Improvement (PhD)

Meta; Menlo Park (CA); In loco; USD 55.000 - 83.000; Tempo pieno

Descrizione del lavoro

Meta is seeking Research Interns for the FAIR team within the MS-Lab to advance video generation, multimodal AI, and post-training of large-scale models. Interns will collaborate with interdisciplinary teams to push perceptual and generative foundations for next-gen AI systems, with multiple start dates yearly.

Responsibilities include researching generative video models, post-training optimization, LLM/VLM pipelines, and publishing findings while supporting Meta product development.

Competenze

• Currently has or is in the process of obtaining a PhD degree in Computer Science, Electrical Engineering, Computer Vision, Machine Learning, Artificial Intelligence, relevant technical field, or equivalent

Mansioni

• Conduct fundamental and applied research in video generation, including generative models, video synthesis, and multimodal learning

Conoscenze

Video generation experience

Multimodal AI

Research experience

Python/C++ proficiency

Formazione

PhD in CS/EE/ML

Strumenti

PyTorch

TensorFlow

Descrizione del lavoro

About

Meta is seeking Research Interns to join the Fundamental AI Research (FAIR) team within Meta Superintelligence Labs (MSL). Our mission is to advance the science of intelligence and develop technologies that push the boundaries of AI. We are looking for individuals interested in video generation, post-training of large-scale models, and self-improving agentic systems to help build the perceptual and generative foundations for next-generation AI systems. This internship offers the opportunity to collaborate with a highly interdisciplinary team of scientists, engineers, and cross-functional partners, leveraging cutting-edge technology, resources, and research facilities. Our interns have the opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.We're especially interested in candidates with expertise across video generation, computer vision, and multimodal AI, including:Generative modeling for video (diffusion, flow matching, video synthesis)Post-training of large-scale video and multimodal models (SFT/RL, optimization, data curation)Multimodal understanding, reasoning, and generationSelf-improving and agentic systems (multi-agent LLM/VLM systems, tool use, planning)Reward modeling and LLM/VLM-as-a-judgeOur team at Meta AI offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year. To learn more about our research, visit https://ai.meta.com/research/.

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, including reinforcement learning from human and AI feedback and reward modeling.
• Research self-improving and agentic generation systems, including multi-agent LLM/VLM pipelines and LLM/VLM-as-a-judge.
• Collaborate with teams across Meta to build perceptual foundations for real-time embodied agents and conversational AI.
• Contribute to the development of frontier models (e.g., Llama, LMMs) and push the boundaries of video and media generation.
• Brainstorm with research mentors, review literature and existing solutions of a challenging real-world research problem.
• Develop novel solutions, implement prototypes, and perform extensive experiments to test the proposed solutions in meaningful benchmarks and metrics, analyze the results and verify the 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.

Minimum Qualifications

• Currently has or is in the process of obtaining a PhD degree in Computer Science, Electrical Engineering, Computer Vision, Machine Learning, Artificial Intelligence, 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 in Python, C++, or other related languages, and deep learning frameworks (e.g., PyTorch, TensorFlow)
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Demonstrated research and software engineering experience via internships, industry or academic work experience, coding competitions, or widely used contributions in open source repositories (e.g., GitHub)
• Experience with video generation, video synthesis, or multimodal fusion techniques
• Experience with video-language models and architectures relevant to video generation and post-training
• Experience with LLM/VLM agents, reward modeling, or evaluation of generative models
• Proven track record of achieving significant results, as demonstrated by grants, fellowships, patents, or publications at leading workshops, journals, or conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV)
• Experience manipulating and analyzing complex, large scale, high-dimensionality 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 degree-program after the completion of the internship/co-op