AI Research Scientist, Multi-Agent Memory - FAIR, MSL

Meta's Fundamental AI Research (FAIR) organization is seeking a Research Engineer to join the team working on multi-agent systems and memory. The role involves driving fundamental breakthroughs to enable agents to reason, learn from experience, and collaborate on complex tasks, contributing across the full spectrum of research, engineering, and deployment for both product and frontier model efforts.Design and execute large-scale research experiments to push the state-of-the-art in machine intelligence, language models, multi-agent communication, test-time scaling, and recursive self-improvement Steer projects from early exploration through evaluation on benchmark datasets such as SWE-bench, RSI-Exam, and PaperBench Directly contribute to experimental design, harness engineering, maintaining large codebases, running evaluations, and tracking end-to-end performance Publish novel algorithmic techniques at top-tier venues, foster open joint experimentation, and mentor team members Lead cross-functional research initiatives and establish solution recipes that bridge research clusters to production serving environmentsBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience A PhD degree in Computer Science, Mathematics, or a similar discipline Proven track record of publications at top-tier AI and NLP conferences (e.g., NeurIPS, ICML, ICLR, ACL, NAACL, EMNLP) Demonstrated experience with training, fine-tuning, and experimentation on language models and Transformers beyond black-box usage Must be able to obtain work authorization in the country of employment Experience working with deep learning frameworks, building research prototypes, and communicating cross-functionally in a team environment Research experience in long-term memory, multi-agent systems, agent orchestration, self-improvement, or automated scientific research Experience with large language model pre-training, fine-tuning, long-context modeling, context compression, or evaluation pipelines at scale Experience building, evaluating, and designing controlled experiments for language-model agents, including tool use, memory mechanisms, or collaborative workflows Proven track record of achieving significant research results, as demonstrated by publications at leading AI and NLP conferencesMeta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here .Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form .