Research Scientist Intern, Meta Recommendation Systems - Core ML (PhD)

Meta•Seattle, WA

5d•$7,650 - $12,667

About The Position

Meta is seeking Research Scientist Interns to join the Meta Recommendation Systems (MRS) research team. The team advances AI and machine learning technology for recommendation systems across Meta’s Family of Apps, including Facebook, Instagram, and WhatsApp. Interns conduct cutting-edge research on AI for recommendation systems, with potential impact at Meta scale. Areas include multimodal content understanding, modeling user interests and preferences, agentic AI, recursive self-improvement, and ecosystem values. The work uses audio, visual, text, and metadata signals associated with posts and videos to improve recommendation relevance and user experience. The team builds tools, frameworks, and models for deployment 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 have or be in the process of obtaining a Ph.D. in Computer Science, Machine Learning, Computer Vision, Artificial Intelligence, or a relevant technical field.
Obtain work authorization in the country of employment by the time of hire and maintain ongoing work authorization during employment.
Experience with Python and machine/deep learning libraries such as PyTorch and Transformers.
Familiarity with AI/ML modeling and algorithmic techniques, including components of multimodal LLMs, RAG, LSTM, GRU, Transformers, RL, or acceleration for large-scale use cases, as well as 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 the internship.
A proven 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, 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 use cases.
Conduct original research that may be applied 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.