Research Scientist Intern, Modern Recommendation Systems (PhD)
Meta

Job Info

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 "Modern Recommendation Systems" (MRS) AI Innovation Center. This org brings together a world-class R&D team of researchers, developers, and engineers. The MRS org is developing a unified infrastructure and model service to improve recommendations across Facebook, Instagram and WhatsApp, the "Family of Apps" (FoA). Our interns will have the opportunity to perform research on and even build AI models that will eventually run at the scale of Meta's social network.Our vision is to understand multi-modal content, especially videos, as well user interests/preference. We contribute to the mission of connecting users to the content they enjoy, are inspired by, and that they want to see more of. 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 content understanding.Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.

Research Scientist Intern, Modern Recommendation Systems (PhD) 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 video understanding libraries and models to implement new features and functionality for use internally at Meta

Minimum Qualifications:

• Currently has or is in the process of obtaining a Ph.D. degree in Computer Science or a related field
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
• Experience with Python, with experience in machine learning libraries such as Pytorch
• Familiarity with AI/ML modeling techniques (e.g., LLM, RAG, LSTM, GRU, Transformers) and/or its acceleration for large scale use cases

Preferred Qualifications:

• Intent to return to the degree program after the completion of the internship/co-op
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences such as NeurIPS, ICLR, KDD, ICML, SIGIR, WSDM, RecSys, CIKM, CVPR, ECCV, ACL, EMNLP, ICASSP, or similar
• Experience working and communicating cross functionally in a team environment
• Prior research or project experience in sequence modeling, recommendation systems, or user modeling
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).

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