AI Research Manager - Meta Superintelligence Labs

Meta•Menlo Park, CA

1d•$219,000 - $301,000

About The Position

Meta is seeking a Research Scientist Manager to join Meta Superintelligence Labs (MSL). In this role, you’ll lead the efforts of building and shipping personal superintelligence at the frontier. This is a technical leadership role requiring research expertise, people management skills, and the experience of driving execution on open-ended AI challenges with high reliability. In this role, you will manage teams of researchers and technical leaders working on large-scale AI problems. The evaluations and datasets your team builds will directly impact the research direction and major model lines within MSL, making engineering reliability, rigor, and scalability paramount. You will maintain high velocity across your team while adapting to rapidly shifting priorities as we advance the technical research frontier. You'll need to be flexible and adaptive, guiding your team through a wide variety of problems in the LLM post-training space. If you are excited about defining the capabilities that drive AI progress, have a track record of building high-performing technical research teams, and thrive in fast-paced, high-impact research environments, we encourage you to apply for this exciting leadership opportunity at the core of MSL.

Requirements

PhD degree in Computer Science, Machine Learning, or a related technical field
6+ years of industry experience in AI research, machine learning, or a closely related technical field
4+ years of experience managing teams of researchers or engineers, including experience managing other technical leaders or managers
Experience working on frontier-quality/state-of-the-art Large Language Models. Deep, practical experience in LLM post-training
Demonstrated ability to balance hands-on technical work with people management and strategic planning
Experience communicating technical strategy and research direction to cross-functional stakeholders
Publications at peer-reviewed venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or similar) related to deep learning, language models, or data-centric AI

Nice To Haves

Hands-on experience managing teams that build language model post-training pipelines (SFT/RLHF/RLVR), synthetic data generation, or high-quality evals infrastructure
Experience in implementing or developing environments for agentive workflows (e.g., tool use, web browsing environments, coding sandboxes)
Extensive experience working on long horizon agents, agent tool use, personalization, and/or search
Experience building infrastructure for agentive workflows, tool-use data collection, or reinforcement learning environments
Experience building and scaling large-scale distributed systems and high-throughput data processing pipelines
Experience managing teams in fast-paced research or startup environments

Responsibilities

Team leadership & management: Build, mentor, and grow a team of research scientists and research engineers
Technical Strategy & Execution: Oversee work across the full LLM post-training stack. Influence the technical roadmap and research direction. Translate ambiguous user and product needs into tractable research questions, technical plans, and measurable outcomes
Cross-functional collaboration: Lead complex cross-functional projects end-to-end
Hands-on technical contributions: Maintain technical credibility through hands-on contributions to critical projects. Review code, provide technical guidance, and unblock complex scaling or modeling challenges. Define and maintain clear research quality standards and engineering best practices and engineering standards for the team