Research Scientist Intern, Ranking & Recommendations (PhD)

Meta; Bellevue, Menlo Park, New York (WA, CA, NY); On-site; USD 55,000 - 66,000; Full time

Job summary

Meta is seeking Research Interns to join our Post-Training & Research team within Facebook. The interns will work on problems in ranking and recommendation, content understanding, and post-training of AI models behind agentic experiences on Facebook.

Internships run 12 to 24 weeks with multiple start dates. Candidates should be pursuing a PhD in CS/AI/ML, have work authorization, and show a track record of significant research results. Collaboration with scientists and engineers is expected.

Qualifications

• Pursuing or awarded Ph.D. in CS/AI/ML or related field.
• Experience with Python and deep learning frameworks.
• Familiarity with transformers and large language models.
• Experience building systems using ML/deep learning methods.
• Ability to publish results at leading venues (e.g., NeurIPS, ICML, ACL).
• Proven track record of significant research results (grants, fellowships, patents, publications).

Responsibilities

• Engage in research on ranking, recommendation, and AI agent systems.
• Develop and evaluate ML models including LLMs and multimodal models.
• Collaborate with research scientists and engineers to formulate and test hypotheses.
• Communicate results and contribute to publications or reports.

Skills

Python

Deep learning

Transformers

LLM reasoning

Rankings & recommendations

Multimodal modeling

Research experience

C++

GitHub contributions

Cross-functional collaboration

Education

Ph.D. in Computer Science / AI / ML or related field

Tools

PyTorch

Job description

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 Post-Training & Research team within Facebook.

The team is part of Facebook Discovery, which builds the systems that decide which posts, photos, videos and Reels people see on Facebook. Our team works on ranking and recommendation, content understanding, and post-training of the AI models behind agentic experiences on Facebook. Our interns will have the opportunity to turn open problems in these systems into research questions and work on them with our research scientists and engineers, with the potential for impact on billions of people.

We believe large language models (LLMs) and AI agents will change how recommendation systems are built. We study generative recommendation models that are trained like language models on sequences of user activity. We build ranking models that reason over a person’s history and a set of candidates to rank and compose what that person sees. We use multimodal models to understand the quality and originality of posts and videos. We post-train models with supervised fine-tuning and reinforcement learning from user feedback, both for recommendation and for AI agents on Facebook. We deploy our models together with product and infrastructure teams, and we publish our results to advance the state of the art.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

• Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, 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
• Experience with Python and deep learning frameworks such as PyTorch
• Familiarity with modern AI/ML modeling techniques (e.g., Transformers, deep learning for recommendation, LLMs and LLM reasoning, multimodal models, mixture-of-experts, diffusion models, RAG, AI agents, post-training with SFT and RL)
• Experience building systems based on machine learning and/or deep learning methods
• Intent to return to the degree program after the completion of the internship
• 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, ICML, KDD, SIGIR, WSDM, RecSys, CIKM, ACL, EMNLP, CoLM, CVPR, ICCV, ECCV, or similar venues
• Research experience in one or more of the following areas: LLM reasoning, post-training (SFT, reinforcement learning, reward modeling), AI agents, generative recommendation, diffusion models, ranking and recommendation systems, sequence and user modeling, computer vision, or multimodal content understanding
• Experience training large-scale deep learning models, such as LLMs or recommendation models
• Experience with C++ or with optimizing LLM training and inference
• Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
• Proficiency in using AI coding agents for rapid development and independent problem solving
• Experience working and communicating cross functionally in a team environment