Meta's Fundamental AI Research (FAIR) organization is seeking a postdoctoral researcher 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.
Responsibilities
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
Qualifications
Currently possess or be pursuing a PhD in Computer Science, Mathematics, or a similar quantitative discipline Demonstrated experience with training, fine-tuning, and experimentation on foundation models beyond black-box usage Must be able to obtain and maintain work authorization in the country of employment Ability to communicate complex ideas with peers Hold first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR) Familiarity with PyTorch