Postdoctoral Researcher (PhD) - FAIR - Core Learning

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.

Postdoctoral Researcher (PhD) - FAIR - Core Learning 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

Minimum 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

Preferred Qualifications

• Ability to communicate complex ideas with peers
• Hold first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR)
• Familiarity with PyTorch

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.