Research Scientist Intern, MSL - Agentic Post-Training (PhD)

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization. Meta is seeking Research Scientist Interns to join a post-training team in Meta Superintelligence Labs (MSL).

The team focuses on agentic post-training of Muse foundation models, as part of our mission to build personal superintelligence. Our team’s work covers end-to-end model post-training cycles, including supervised fine-tuning (SFT), reinforcement learning (RL), evaluation, and agentic task and environment creation. We are looking for candidates who are passionate about improving the model's agentic capabilities, including but not limited to long-horizon task completion, complex tool use, search and deep research, and browser use.

As an intern, you will have the opportunity to make core model improvements, apply your ideas at unprecedented scale, and directly shape the user experience of Muse. Our internships are twelve (12) to twenty-four (24) weeks long, and we have various start dates throughout the year. Develop novel, state-of-the-art agentic post-training methods and supporting systems, using deep learning and reinforcement learning techniques.

Work hands-on across the full LLM post-training stack, and execute