Meta is seeking Research Scientist Interns passionate about understanding and improving state-of-the-art AI systems, making key contributions to research on fairness, inclusion, and the reliability of modern machine learning approaches. We operate across modalities, and are deeply committed to understanding the impacts of AI in real-world social contexts. We welcome applications from those with experience in diverse subject areas including but not limited to responsible AI, computer vision, audio and speech processing, and natural language processing.We offer twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.

Research Scientist Intern, Responsible AI (PhD) Responsibilities:

• Conduct independent research that investigates the practical impacts of generative AI models, including but not limited to benchmarking, empirical evaluations and theoretical contributions.
• Publish state-of-the-art research papers in responsible AI with particular focus on developing fair, inclusive, and reliable AI systems that work well for everyone.
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
• Produce and open source high quality code and reproducible results for the community.

• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
• Experience with Python, PyTorch, and modern frameworks for efficient training, finetuning, or evaluating large-scale generative models.

• Intent to return to a degree program after the completion of the internship/co-op.
• Proven track record of achieving significant results as demonstrated by grants, fellowships, or patents, as well as publications in publications at leading workshops or conferences such as NeurIPS, ICLR, ICML, *ACL, EMNLP, FAccT, AIES, or similar. Contributions to affinity workshops are welcome.
• Demonstrated experience and self-driven motivation in solving novel, complex problems.
• Demonstrated software engineering experience via an internship, work experience, coding competitions, or contributions to open-source repositories (e.g., on GitHub).
• Experience working and communicating cross-functionally in a team environment.
• Interest or experience in communicating across disciplines, incorporating diverse perspectives, and conducting interdisciplinary research.