AI Research Scientist, MRS Knowledge

The AI Research Scientist role conducts novel research and develops advanced machine learning models, particularly in large language models, and recommendation systems, to drive innovation in content and user understanding, retrieval, and ranking. These deliverables directly enhance Meta’s products by powering more accurate, efficient, and personalized recommendations across Facebook, Instagram, Threads, and other platforms. By advancing AI research and development, the role supports Meta’s business growth, improves user experiences, and enables scalable solutions that benefit Meta’s customers and people.

Responsibilities

• Collaborate and execute on research that pushes forward the state of the art in large language model research
• Directly contribute to experiments, including designing experimental details, running evaluations, and organizing results
• Contribute to publications and open-sourcing efforts
• Help identify long-term research goals as well as intermediate milestones
• Prioritize research that can be applied to Meta's product development

Minimum Qualifications

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Currently has, or is in the process of obtaining a PhD degree in Computer Science, Artificial Intelligence, Data Science, or related technical fields
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Experience working and communicating cross-functionally in a team environment
• Experience with applying reinforcement learning techniques to production scale systems
• Experience in ranking, recommendation, or auction systems
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences
• Prior work bridging academic research and real-world applications