AI Research Intern: Post-Training & Recommender Systems

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 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.