Lead AI Research Scientist – LLM Post-Training & Agents

Meta; Menlo Park (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Meta is seeking AI researchers for the Modeling & ToolCalling team within Meta Superintelligence Labs, focusing on LLM post-training, long-horizon agentic tool use, search, and personalization to enable real-world model operation.

Candidates will have strong PhD progress or completed PhD, multiple peer-reviewed publications, and proven leadership on large AI projects, with deep hands-on experience in LLM post-training and frontier models.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Currently has, or is in the process of obtaining, a PhD degree in Computer Science or a related technical field
• 2+ years of industry research experience in LLM/NLP, computer vision, or related AI/ML models
• Deep, practical experience in LLM post-training
• Experience as a technical lead on a team and/or leading complex technical projects from end to end
• Published research in leading peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV) and/or demonstrated significant industry influence in the field of AI
• Extensive experience working on long horizon agents, agentic tool use, personalization, and/or search
• Experience working on frontier-quality, state-of-the-art Large Language Models
• First-author publications at top peer-reviewed conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ICCV)

Education

Bachelor's degree in Computer Science or related field

PhD in Computer Science or related field

2+ years industry research in AI/ML/LLM/vision

Technical leadership / project leadership

Publications in top conferences

Experience with long-horizon agents and tool use

Experience with frontier-state LLMs

First-author publications at top conferences

Job description

Meta is seeking AI researchers for the Modeling & ToolCalling team within Meta Superintelligence Labs, focusing on LLM post-training, long-horizon agentic tool use, search, and personalization to enable real-world model operation.

Candidates will have strong PhD progress or completed PhD, multiple peer-reviewed publications, and proven leadership on large AI projects, with deep hands-on experience in LLM post-training and frontier models.