AI Research Scientist

About the Role

Meta is seeking a Research Scientist to join the Fundamental AI Research (FAIR) team within Meta Superintelligence Labs (MSL). This role 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.

Key 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, improving their performance, robustness, and generalization.
• Collaborate with teams across Meta to build perceptual foundations for real-time embodied agents and conversational AI.
• Contribute to the development and deployment of frontier models (e.g., Llama, LMMs) and push the boundaries of video and media generation.

Requirements & Tech Stack

• Demonstrated expertise in video generation, computer vision, or multimodal AI.
• Experience with large-scale model training, post-training optimization techniques, and data curation.
• Publication record in relevant fields.
• 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.
• 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 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.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• PhD or equivalent experience in Computer Science, Electrical Engineering, or a related field.