Research Scientist Intern, Ranking & Recommendations (PhD)

Job description

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 Interns to join our Post-Training & Research team within Facebook. The team is part of Facebook Discovery, which builds the systems that decide which posts, photos, videos and Reels people see on Facebook. Our team works on ranking and recommendation, content understanding, and post-training of the AI models behind agentic experiences on Facebook. Our interns will have the opportunity to turn open problems in these systems into research questions and work on them with our research scientists and engineers, with the potential for impact on billions of people. We believe large language models (LLMs) and AI agents will change how recommendation systems are built. We study generative recommendation models that are trained like language models on sequences of user activity. We build ranking models that reason over a person’s history and a set of candidates to rank and compose what that person sees. We use multimodal models to understand the quality and originality of posts and videos. We post-train models with supervised fine-tuning and reinforcement learning from user feedback, both for recommendation and for AI agents on Facebook. We deploy our models together with product and infrastructure teams, and we publish our results to advance the state of the art. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.