Research Scientist Intern, Meta Recommendation Systems

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 Meta Recommendation Systems (MRS) Research. This newly created org brings together a world-class team of AI Research Scientists and Engineers. The MRS Research org is exploring and advancing SoTA technology, centering around AI and ML, to arrive at a unified infrastructure and model service to leapfrog recommendation systems (Recsys), its theory and algorithms across Meta (Facebook, Instagram and WhatsApp, the “Family of Apps” (FoA)). Our interns will have the opportunity to perform cutting-edge research on AI for Recsys with the potential to have an impact at Meta’s scale. Our vision is to leverage AI frontier models in all aspects of recommendation systems including but not limited to deep understanding of multi-modal content (especially images/videos, posts, user interactions), modeling user interests and preference, values of the ecosystems. We contribute to the mission of connecting users to the content they enjoy, are inspired by, and that they want to see more of. To this end, we conduct cutting-edge research using the complete suite of audio, visual, text and metadata signals associated with posts and videos to improve recommendation relevance across all surfaces and provide a better, more meaningful experience to users. We build tools, create frameworks and train models that we deploy together with product and infrastructure teams to gain adoption across the FoA. We also publish scientific papers to help advance the state of the art in all aspects of the technology stack. Responsibilities • Initiate and lead efforts towards long-term ambitious research goals, while identifying intermediate milestones in the area of recommendation systems and models, user and content understanding and multi-modal (video, audio, and text) LLM analysis for classification and relevance use cases. • Conduct original research that can eventually be applied to Meta product development, engage with the wider research community, including publishing and releasing open source software where appropriate. • Design, train and support AI/ML libraries and models to implement new features and functionality for use internally at Meta. • Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results. Minimum Qualifications • Currently has or is in the process of obtaining a Master’s degree in Computer Science, Computer Vision, Artificial Intelligence, or relevant technical field • Experience with Python, with experience in machine learning libraries such as Pytorch • Experience building systems based on machine learning and/or deep learning methods • Prior research or project experience in LLM, Computer Vision, Artificial Intelligence, or relevant technical field Preferred Qualifications • Experience solving complex problems and comparing alternative solutions, trade offs, and varied points of view to determine a path forward • Demonstrated experience in building large scale recommendation systems • Experience working and communicating cross-functionally in a team environment • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as RecSys, CVPR, ICCV/ECCV, ICLR, ICML or NEURIPS Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.