Research Scientist Intern, Youth Safety (PhD)
About The Position
Meta is seeking a Research Intern to join the Youth and Controls team within Facebook. The team develops age-appropriate content experiences across Facebook, including content-understanding and age-understanding models used across Teen Accounts, parental supervision, U13 experiences such as Messenger Kids, and protective content tiers. The role addresses high-impact problems at the intersection of machine learning, integrity, and personalization, including harmful-content detection for youth, age-appropriate ranking and retrieval, safety-aware personalization and controls, and reconciliation of stated and predicted age signals. A cross-cutting focus is evaluation at scale: building LLM-judge and quality-evaluation infrastructure for enforcement LLMs, and connecting model improvements to teen experience through human judgments and online experiments. Internships last 12 to 16 weeks, or 24 weeks, with various start dates throughout the year.
Requirements
- Currently pursuing a PhD; the role is identified as a PhD internship.
- Demonstrated software development experience through technical internships, work experience, coding competitions, or widely used contributions to open-source machine-learning repositories.
- Experience working and communicating cross-functionally in a fast-paced team environment.
- Ability to frame real-world safety problems as rigorous machine-learning problems and drive iterations based on clear analysis.
- Interest in youth safety or integrity as a research domain and comfort owning a problem end-to-end, from hypothesis to shipped model.
Nice To Haves
- Intent to return to the degree program after completing the internship or co-op.
- A strong research record demonstrated by grants, fellowships, patents, or publications at leading AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, KDD, CVPR, SIGIR, WWW, or similar.
- Prior research or project experience in trust and safety, integrity or abuse detection, content understanding, age modeling and verification, age-appropriate recommendation, personalization, LLM-based evaluation or LLM judges, reinforcement learning, pre-training or fine-tuning large language models, or multimodal understanding.
Responsibilities
- Perform research to advance intelligent-machine science and technology as applied to youth safety and integrity.
- Develop novel content-understanding, age-understanding, retrieval, ranking, and personalization models for age-appropriate experiences.
- Advance proactive enforcement approaches, including reducing reliance on human review while maintaining quality and safety.
- Develop training and evaluation methods using human judgments, LLM judges, and online experiments to improve safety, quality, and downstream experience.
- Analyze and improve the efficiency, scalability, latency, and stability of safety models in production serving.
- Collaborate with researchers and cross-functional partners, communicating research plans, progress, and results.
- Publish research results and contribute research applicable to Meta product development.
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
