Meta is seeking Research Interns to join the Modern Recommendation Systems (MRS) AI Innovation Center to develop a unified infrastructure and model service to improve recommendations across Facebook, Instagram, and WhatsApp
Requirements
- 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
- Experience building systems based on machine learning and/or deep learning methods
- Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Computer Vision, Artificial Intelligence, or relevant technical field
- 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)
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
- Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
Other
- Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Computer Vision, Artificial Intelligence, or relevant technical field
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Intent to return to the degree program after the completion of the internship/co-op
- 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 publications at leading workshops or conferences
