Meta is seeking a hands-on technical leader to advance Personal Superintelligence within Meta Superintelligence Labs (MSL). This role focuses on turning ambiguous, real-world product problems into shipped systems and measurable improvements in frontier-model capabilities, including long-horizon agents, tool use, full-stack coding, search, and personalization. In this role, you will work across the full research-to-product stack-from user experiences, backend systems, and agent environments to data, evaluations, post-training, and deployment, collaborating across research, product, design, engineering, data, and infrastructure to identify high-leverage opportunities and deliver tangible impact within clear timelines.
Responsibilities
Work hands-on across the full LLM post-training stack
• Build high-quality training data and design and run rigorous, product-relevant evaluations
• Execute, analyze, and iterate on large-scale post-training runs
• Own end-to-end model capability hill-climbing, from identifying gaps through data, training strategy, evaluation, deployment, and product feedback
• Advanced long-horizon agent capabilities, including tool use, full-stack coding, search, planning, and personalization
• Develop realistic harnesses, environments, and evaluations for agentive tasks spanning code understanding, implementation, testing, debugging, and tool use
• Research improved training, evaluation, synthetic-data generation, and data curation strategies
• Translate ambiguous user and product needs into tractable research questions, technical plans, and measurable outcomes
• Lead complex cross-functional projects end-to-end while remaining deeply involved in implementation, experimentation, and analysis
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's or Master's degree in a relevant technical field, or equivalent practical experience
• 6 years of experience in machine learning engineering, AI research, software engineering, or a related field
• 4 years of providing technical leadership for complex, multi-person projects
• Experience in developing or improving frontier-quality large language models or related foundation models
• Deep, hands-on experience with state-of-the-art LLM post-training, data generation, evaluation, experimentation, and model behavior analysis
• Track record of solving ambiguous, real-world problems and delivering measurable impact within defined timelines
• Ability to work independently, lead across functions, and adapt quickly as evidence and priorities evolve
Preferred Qualifications
• Publications at leading peer-reviewed venues such as NeurIPS, ICML, ICLR, ACL, or EMNLP, or equivalent have demonstrated industry impact in AI
• Experience taking model capabilities from research prototypes to production products
• Experience with large-scale distributed systems and high-throughput data pipelines
• Experience developing agent harnesses, realistic environments such as web browsers or coding sandboxes, and associated evaluations
• Extensive experience with long-horizon agents, agentive coding, tool use, personalization, or search
