Research Scientist Intern, Integrity AI (PhD)

Meta • Seattle, WA

7d • $7,650 - $12,667

About The Position

Meta is seeking Research Interns to join the Entity and Actor Integrity team within Facebook Integrity. The team develops applied machine learning systems that enforce policies concerning entities and the actors who run them, including groups, pages, events, and creators. Its models determine when entities should be removed, when engagement is inauthentic, when pages impersonate others, and when enforcement decisions should be reversed on appeal.

The team is advancing from per-post classifiers to large-language-model-based systems that reason over an entity’s content, members, administrators, and history. The research focuses on making decisions efficient, reliable, and continually improving—for example, distilling large reasoning models into smaller, faster models, maintaining shared multi-harm models without regressions, learning from scarce expert labels, calibrating confidence to support deferral, and measuring quality when models outperform many human reviewers. Interns take ownership of a focused research problem from framing through experimentation and publication, with guidance from research scientists and machine learning engineers.

Requirements

• Currently has or is in the process of obtaining a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Computer Vision, Statistics, or a relevant technical field.
• Must obtain work authorization in the country of employment by the time of hire and maintain ongoing work authorization during employment.
• Experience with Python.
• Experience with deep learning frameworks such as PyTorch.
• Machine learning research experience, including training or fine-tuning deep learning models and designing experiments to evaluate them.
• Familiarity with large language models and AI-native development tools such as Claude or Codex.

Nice To Haves

• Intent to return to the degree program after completion of the internship or co-op.
• Research achievements demonstrated by publications at leading venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, COLM, CoLLAs, KDD, WWW, or ICWSM.
• Research or project experience in one or more of continual or lifelong learning, multi-task learning and model merging, active learning, knowledge distillation, LLM post-training (SFT, preference optimization, RL), uncertainty estimation and calibration, learning from AI feedback or LLM judges, multimodal modeling, or sequence/graph modeling of user behavior.
• Experience applying machine learning to trust and safety, content moderation, fraud, or abuse detection.
• Experience with large-scale or parameter-efficient training, such as LoRA or distributed training.
• Demonstrated software development experience through internships, work experience, coding competitions, or widely used open-source contributions.
• Experience working and communicating cross-functionally in a fast-paced environment, with the ability to frame real-world problems as rigorous machine learning problems and drive iterations from clear analysis.

Responsibilities

• Perform research to advance the science and technology of trustworthy, efficient AI systems for integrity and safety.
• Develop novel methods for training, distilling, and continually updating large language and multimodal models that make policy decisions about entities and actors.
• Design rigorous experiments and evaluations using expert human labels, LLM judges, and offline replays, including methods that remain valid when labels are scarce or expensive.
• Analyze and improve the efficiency, calibration, robustness, and reliability of models used in production enforcement.
• Collaborate with researchers, engineers, and policy partners, communicating research plans, progress, and results.
• Publish research results and contribute to research that can be applied to Meta product development.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree