Meta Superintelligence Labs is seeking a Research Scientist Manager to lead a high-impact team working on the next generation of AI Assistants powered by frontier-scale foundation models. This role centers on building cutting-edge measurement and evaluation paradigms that align fast-moving model development with real end-user value. As a Research Scientist Manager, you will define the scientific strategy behind the evaluation flywheel, ensure scientific across methodologies, and partner with product, engineering, and model training teams to steer the system toward reliability and trustworthiness at scale.
Responsibilities
Define and execute the scientific roadmap for measurement of AI Assistant with purpose, agility, and efficiency Lead the development of innovative offline and online evaluation metrics, benchmarks, and data synthesis methodologies to drive model improvement and improve user experience Partner closely with research, engineering, and product teams to integrate robust measurement into the model development lifecycle (the "evaluation flywheel") Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects Mentor and grow a team of Industry-Leading research scientists and applied scientists, fostering a of scientific rigor, impact, and success
Qualifications
12+ years of, or PhD + 8 years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development Experience and track record of landing large research and/or product impacts in a time-sensitive environment 2+ years of people-management experience leading research scientists or applied scientists Proven technical vision in where the field of generative AI will go Experience of and knowledge of online and offline measurement, benchmark building, and data synthesis Experience with cross functional collaboration with other teams including non-engineering functions Demonstrated experience recruiting, building, structuring, leading technical organizations, including performance management PhD or equivalent research experience in fields such as machine learning, statistics, econometrics, causal inference, computer science, optimization, or related areas Experience developing evaluation frameworks for LLMs, multimodal models, or interactive assistants Expertise in online measurement, user-behavior modeling, A/B testing, and experiment platform design Experience building large-scale datasets and ontologies used for training or evaluation Background in safety, alignment, content evaluation, or human-AI interaction Ability to communicate complex ideas clearly to executives, product partners, and engineering stakeholders Proven ability to build high-performing teams that thrive under ambiguity and rapid iteration Experience with cross functional collaboration with other teams including non-technical functions Demonstrated experience recruiting, building, structuring, leading technical organizations, including performance management