AI Research Scientist (Technical Leadership), Multimodal - Monetization GenAI

The Monetization GenAI Video Gen & Visual Search group, part of the Ads pillar, is building the next generation of generative AI for video - from creation to understanding to transformation - at a scale that reaches billions of users. We develop proprietary foundation models for video generation, video-to-video editing, audio generation (music, voiceover, dubbing), and multimodal video understanding powered by large language models. We produce industry leading video models, and our research translates into products that drive hundreds of millions of dollars in annual advertising revenue. We are looking for a technical leader in AI research to define the research vision across video and audio generation, drive breakthrough research, and shape the technical direction of the organization., 1. Lead end-to-end AI research and model development for video-centric generative AI across Meta’s advertising surfaces

1. Drive advancements in video generation & enhancement
2. Develop video-to-video & audio generation capabilities
3. Advance video & visual understanding through novel research
4. Conduct foundation model research to support generative AI innovation
5. Define research agendas and pioneer new directions in video/audio generation and multimodal understanding

AI Research Scientist (Technical Leadership), Multimodal - Monetization GenAI Responsibilities, 1. 4+ years of experience training large language and/or vision models, with extensive and recent experience training multimodal LLMs

1. Research expertise in video generation/understanding, multimodal learning, or diffusion models
2. Demonstrated significant industry influence in the field of AI and/or recently published research in leading peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV), 1. First-author publications at top peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV)
3. Experience working on frontier-quality/state-of-the-art MLLM
4. Experience with audio/speech generation or processing
5. Experience with unified/multi-task foundation model architectures
6. Industry research lab experience