AI Research Scientist, Text Data Research - MSL FAIR

Summary: Meta is seeking AI research scientists to help us build the data foundation for Meta's most advanced Large Language Models. The role involves collaborating with cross-functional teams to develop foundational models and tackling data challenges at scale. 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 - Architect efficient and scalable data curation systems and pipelines - 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 agentic data, synthetic data, reasoning data, web parser, coding data, data scaling laws, or datamix optimization - Lead complex technical projects end-to-end Required 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 - 1+ year of industry research experience in LLM/NLP or related AI/ML models - Experience owning and/or driving complex technical projects from end-to-end - Practical experience with pre-training or mid-training data curation for large foundational models and experience working with organic, synthetic, agentic, or reasoning data for LLMs - Published research in leading peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP) and/or demonstrated significant industry influence in the field of AI Preferred Qualifications: - Experience working on frontier-quality/state-of-the-art Large Language Models - Multiple first-author publications in leading peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP) - Hands-on experience with modeling frameworks like PyTorch - Hands-on experience on SQL and large-scale data handling, with familiarity of frameworks like Spark and Hive Required Skills: LLM expertise, data curation, synthetic data generation Important Skills: PyTorch, SQL, large-scale data handling Nice-to-Have Skills: research publication, collaboration, project management Benefits: Bonus, Equity, Benefits