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Meta's Fundamental AI Research (FAIR) organization is seeking a Research Scientist to drive advancements in generative models, with a particular focus on fundamental topics (data efficiency, continual learning) in large language models (LLMs) research. The role involves working across the full spectrum of research, engineering, and deployment for both product and frontier model efforts.
Job Responsibility:
Innovate, lead, and execute pioneering research to push the state-of-the-art in generative models and LLM performance
Systematically perform independent research, quickly adapting to new developments in the field
Directly contribute to the experimental process, including designing details, implementing reusable code, running evaluations, and organizing results
Contribute to publications, open-sourcing initiatives, and mentor other team members
Ensure effective cross-functional collaboration
Requirements:
A PhD in Computer Science, Mathematics, or a similar quantitative discipline
Hold first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR)
Demonstrated experience with training, fine-tuning, and experimentation on foundation models beyond black-box usage
Familiarity with PyTorch
Must be able to obtain and maintain work authorization in the country of employment
Nice to have:
Ability to conduct independent research, communicate complex ideas with peers