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 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 environmentsMeta builds technologies that help people connect, find communities, and grow businesses. 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.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.