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.
Responsibilities
Collaborate with cross-functional teams to develop Meta’s next foundational models Advance our understanding of data research, such as how to overcome data walls and how best to create synthetic data Fundamentally improve our data velocity across workflows and projects by contributing to the advancement of data tooling Execute on high priority projects in pre-training, mid-training, or post-training data curation Apply specialized expertise in video/image generation, video/image perception, OCR, data scaling laws, or data mixing Lead complex technical projects end-to-end
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience PhD in Computer Science or a related technical field 2+ years of industry research experience in LLM/NLP, computer vision, or related AI/ML models Experience as a formal technical lead, leading major technical initiatives with cross-functional impact, and/or influencing strategy across multiple teams 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, DataFlow) Familiarity with SQL and file formats, such as Hive, Iceberg, Parquet, etc