AI Research Manager - Meta Superintelligence Labs

Meta; Menlo Park (CA); Híbrido; USD 190.000 - 270.000; Jornada completa

Descripción de la vacante

Meta is seeking a Research Scientist Manager to lead Meta Superintelligence Labs (MSL). You will manage teams of researchers and technical leaders tackling large-scale AI problems, shaping model directions and evaluation infrastructure.

The role blends hands-on research with strategy, prioritizing reliability, scalability, and cross-functional collaboration to advance frontier AI capabilities.

Formación

• PhD required with 6+ years in AI research or related field.
• 4+ years of experience managing teams of researchers or engineers, including technical leaders.
• Experience with frontier-quality LLMs and post-training pipelines (SFT/RLHF/RLVR).

Responsabilidades

• Lead teams of researchers and technical leaders on large-scale AI problems.
• Balance hands-on technical work with people management and strategic planning.
• Drive execution on open-ended AI challenges with high reliability and impact.
• Build and scale infrastructure for agentive workflows and evals pipelines.

Conocimientos

Team leadership

LLM research

Deep learning

Post-training LLM

Agentive workflows

Data pipelines

Publications

Cross-functional communication

Reinforcement learning

Educación

PhD in Computer Science, Machine Learning, or related technical field

Descripción del empleo

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.

PhD degree in Computer Science, Machine Learning, or a related technical field6+ years of industry experience in AI research, machine learning, or a closely related technical field4+ years of experience managing teams of researchers or engineers, including experience managing other technical leaders or managersExperience working on frontier-quality/state-of-the-art Large Language Models. Deep, practical experience in LLM post-trainingDemonstrated ability to balance hands‑on technical work with people management and strategic planningExperience communicating technical strategy and research direction to cross‑functional stakeholdersPublications at peer‑reviewed venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or similar) related to deep learning, language models, or data‑centric AI Hands‑on experience managing teams that build language model post‑training pipelines (SFT/RLHF/RLVR), synthetic data generation, or high‑quality evals infrastructureExperience 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 searchExperience building infrastructure for agentive workflows, tool‑use data collection, or reinforcement learning environmentsExperience building and scaling large-scale distributed systems and high‑throughput data processing pipelinesExperience managing teams in fast‑paced research or startup environments