AI Research Scientist, Media Data Research - MSL FAIR
Listed on 2026-08-02
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IT/Tech
Data Scientist, AI Business & Operations, AI Engineer (Applied/Software), AI Evaluation
Meta is seeking AI research scientists to help us build the data foundation for Meta's most advanced Large Language and Media Models. We're looking for researchers with LLM/LMM expertise to join us on working with data at scale and to push beyond the data ceiling. Our team contributes to data curation across all stages of LLM/LMM development (pre-training, mid-training, post-training) and all domains/modalities (image, video, agent, media perception and generation).
We are tackling complex challenges at trillion-scale, including organic data curation, synthetic data generation, agent and interaction data, and frontier paradigms that redefine what is possible.
Based in Meta Superintelligence Labs (MSL) within the Fundamental AI Research Organization (FAIR), you'll directly contribute to Meta's frontier models like Llama, while having the chance to collaborate with researchers and engineers across MSL.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- PhD in Computer Science or a related technical field
- 1+ year of industry research experience in LLM/LMM, computer vision, or related AI/ML models
- Experience owning and/or driving complex technical projects from end-to-end
- Practical experience with multimodal pre-training or mid-training data curation for large media perception or generation models
- Published research in leading peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV) and/or demonstrated significant industry influence in the field of AI
- Experience working on frontier-quality/ state-of-the-art Large Language or Large Media Models
- First-author publications at top peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV)
- Programming experience in Python and hands-on experience with frameworks like PyTorch or Spark, or related distributed computing frameworks (Ray, Data Flow)
- Familiarity with SQL and file formats, such as Hive, Iceberg, Parquet, etc
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