Research Scientist Intern PhD

About the Role

Meta is seeking Research Interns to join our Safety Evals and Red Teaming team within the Products and Applied Research org. This is a 16-week internship with various start dates throughout the year.

What You Could Work On

Projects may address questions such as:

• How reliably do LLM-based judges identify safety-policy violations across different tasks, prompts, and adversarial conditions? How should we measure their errors and consistency?
• How should we evaluate prompt-injection risks when an agent interacts with tools and untrusted information? Which environments and attack scenarios expose failures that simpler tests miss?
• Which automated red teaming methods uncover meaningful safety failures, and how well do those failures generalize beyond the prompts or environments used to find them?
• How can we use synthetic data and benchmark design to improve coverage while checking that scores reflect the behavior we intend to measure?

Key Responsibilities

• Formulate a focused research question about content safety, agent security, or the reliability of safety evaluations.
• Design controlled experiments, evaluation datasets, or agent environments that test the question and account for relevant limitations.
• Implement and run experiments, including evaluation harnesses, automated attacks, synthetic data generation, or LLM-based judging methods.
• Collaborate with researchers and cross-functional partners to connect research findings with safety-policy requirements and product development.
• Communicate research plans, progress, and results through clear documentation and presentations, and contribute to research publications applicable to Meta's products.

Requirements & Tech Stack

• Research experience in safety, red-teaming, evals, machine learning, deep learning, computer vision, and/or natural language processing.
• Experience with Python, C++, C, Java or other related languages.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

Preferred Qualifications

• Experience in one or more areas relevant to the team: model evaluation, LLM safety or alignment, agent security, prompt injection, automated red teaming, synthetic data generation, LLM-based judging, or evaluation science.
• Experience designing ML experiments, analyzing complex datasets, and using quantitative approaches to investigate research questions.
• Substantial research contributions through first-author publications at leading workshops or conferences such as NeurIPS, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, or similar.
• Demonstrated software engineering experience through internships, employment, coding competitions, or contributions to widely used open-source projects.
• Experience collaborating with teams and communicating technical results to non-technical audiences.
• Intent to return to the degree program after the completion of the internship/co-op.