Research Scientist Intern, Meta Recommendation Systems (PhD)
About The Position
Meta is seeking Research Interns to join Meta Recommendation Systems (MRS), a team of AI Research Scientists and Engineers advancing AI and machine learning for recommendation systems across Meta’s Family of Apps: Facebook, Instagram, and WhatsApp. Interns will conduct cutting-edge research on AI for recommendation systems, with the potential to affect products at Meta’s scale. Research areas include using frontier AI models and technologies for multimodal content understanding, modeling user interests and preferences, agentic AI, recursive self-improvement, and ecosystem values. The team uses audio, visual, text, and metadata signals from posts and videos to improve recommendation relevance and user experience. It builds tools, frameworks, and models in partnership with product and infrastructure teams, and publishes research to advance the field. Internships last 12 to 24 weeks, with various start dates throughout the year.
Requirements
- Currently has or is pursuing a Ph.D. in Computer Science, Machine Learning, Computer Vision, Artificial Intelligence, or a relevant technical field.
- Must obtain work authorization in the country of employment by the time of hire and maintain it during employment.
- Experience with Python and machine/deep learning libraries such as PyTorch and Transformers.
- Familiarity with AI/ML modeling and algorithmic techniques, such as multimodal LLM components, RAG, LSTM, GRU, Transformers, RL, or acceleration for large-scale use cases, and emerging technologies such as agentic AI, RSI, and autoresearch.
- Experience building systems based on machine learning and/or deep learning methods.
Nice To Haves
- Intent to return to the degree program after completing the internship.
- A track record of significant results demonstrated through grants, fellowships, patents, or publications at leading workshops or conferences such as NeurIPS, ICLR, KDD, ICML, SIGIR, WSDM, RecSys, CIKM, CVPR, ECCV/ICCV/WACV, ACL, EMNLP, ICASSP, or CoLM, or similar venues.
- Experience working and communicating cross-functionally in a team environment.
- Prior research or project experience in sequence modeling, recommendation systems, user modeling, or RL.
- Prior research or project experience with LLMs, such as pre/mid-training, alignment, post-training, or RLVR, and agents, such as meta-harness or self-evolving agents.
- Demonstrated software engineering experience through an internship, work experience, coding competitions, or widely used open-source contributions.
Responsibilities
- Initiate and lead efforts toward long-term research goals, identifying intermediate milestones in recommendation systems and models, user and content understanding, and multimodal LLM analysis for classification and relevance.
- Conduct original research with potential application to Meta product development, engage with the wider research community, and publish or release open-source software where appropriate.
- Design, train, and support AI/ML libraries and models to implement new features and functionality for internal use at Meta.
- Collaborate with researchers and cross-functional partners, communicating research plans, progress, and results.
Benefits
- Benefits are offered; specific benefits are not listed.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
