Meta is seeking Research Scientists to join the Product and Applied Research organization within MSL (Meta Superintelligence Lab). This role requires industry experience working on LLM post-training and the ability to apply relevant AI techniques to build intelligent rich language systems that improve Meta's products and experiences.

Responsibilities

• Help advance the science and technology of intelligent machines
• Work on research projects, strategies, and problems of moderate to high complexity and scope. Identify and define both short- and medium-term objectives
• Influence progress of relevant research communities by producing publications
• Establish strong connection with cross-functional partners and contribute research with the goal of applying to Meta's product development
• Lead and collaborate on research projects within a team
• Design policies, processes, procedures, methods, tests, and/or components, from the ground up for end-to-end systems
• Apply in-depth knowledge of how the machine learning system interacts with the other systems around it

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Ph.D. and publications in machine learning, AI, computer science, statistics, applied mathematics, data science, or related technical fields
• Proven track record of recent and consistent publication/citation history
• Experience leading a team in solving modeling problems using AI/ML approaches
• Experience in applying research to production problems
• Experience communicating research for public audiences of peers

Preferred Qualifications

• 4+ years of experience conducting AI research post PhD
• 4+ years of experience as a tech lead in leading complex technical projects from end to end
• Experience working on frontier-quality/ state-of-the-art Large Language Models
• Experience bringing machine learning-based products from research to production
• First-author publications at peer-reviewed AI conferences (e.g., NeurIPS, ICML, ICLR, AAAI)