• 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.

• Currently has or is in the process of obtaining a PhD degree in Machine Learning, Artificial Intelligence, Computer Science, Information, Reinforcement Learning, Mathematics, or relevant technical field.
• 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.

Preferred qualifications:

• 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.