Research Scientist Intern, Recommendation Systems
Meta
Posted 15 Nov 2026, 06:54 ET
This job at a glance
- Who can apply
- New grads and up to 1 year
- Must know
- Machine learningSocial mediaPythonPyTorchDeep learningComputer vision
- Nice to have
- LLMsGit
- Work
- On-site in Seattle · internship
- Pay
- Not stated by the employer.
- Skill demand
- Python31%Machine learning25%PyTorch11%Social media2%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 15, 2026 · still open
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About Meta
Meta builds technologies that help people connect, find communities, and grow businesses.
About the Role
Meta is seeking Research Interns to join our research team within Meta Recommendation Systems (MRS). This team brings together a world-class team of AI Research Scientists and Engineers, exploring and advancing state-of-the-art technology in AI and ML to improve recommendation systems across Meta's Family of Apps (Facebook, Instagram, and WhatsApp). Interns will have the opportunity to perform cutting-edge research on AI for RecSys with the potential for impact at Meta’s scale. The internship duration is twelve (12) to twenty-four (24) weeks, with various start dates throughout the year.
Key Responsibilities
- Initiate and lead efforts towards long-term ambitious research goals in 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 applicable to Meta product development, engaging with the wider research community through publications and open-source software releases.
- Design, train, and support AI/ML libraries and models for new features and functionality.
- Collaborate with researchers and cross-functional partners, communicating research plans, progress, and results.
Requirements & Tech Stack
- Python
- PyTorch
- Transformers
- Familiarity with AI/ML modeling and algorithmic techniques (e.g., multimodal LLM components, RAG, LSTM, GRU, Transformers, RL, agentic AI, RSI, autoresearch).
- Experience building systems based on machine learning and/or deep learning methods.
Qualifications
- Currently have or be in the process of obtaining a Ph.D. degree in Computer Science, Machine Learning, Computer Vision, Artificial Intelligence, or a relevant technical field.
- Must obtain and maintain work authorization in the country of employment.
Preferred Qualifications
- Intent to return to the degree program after the internship.
- Proven track record of significant results demonstrated by grants, fellowships, patents, and publications at leading workshops or conferences (e.g., NeurIPS, ICLR, KDD, ICML, SIGIR, WSDM, RecSys, CIKM, CVPR, ECCV/ICCV/WACV, ACL, EMNLP, ICASSP, CoLM, or similar).
- 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 (e.g., pre/mid-training, alignment, post-training, RLHF) and agents (e.g., meta-harness, self-evolving agents).
- Demonstrated software engineering experience via an internship, work experience, coding competitions, or contributions to open-source repositories (e.g., GitHub).