Research Scientist Intern, FAIR (PhD)

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.Meta is seeking Research Scientist Interns to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in Responsible AI. We publish groundbreaking papers and release frameworks/libraries that are widely used in the open-source community. Recent examples include the LLaMa family of Large Language Models (LLMs) and tool-augmented language models. We also collaborate with the Meta Generative AI and other organisations to bring the latest research findings to production. We seek Interns to join our research team to foster cutting-edge research in social implications of AI.We offer twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.

• Publish state-of-the-art research papers in responsible AI with particular focus on social impact of AI technologies.
• Conducting independent research that investigates how sociotechnical systems impact various social groups in different ways.
• Open sourcing high quality code and reproducible results for the community.

• Currently has or is in the process of obtaining a Ph.D. 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, C++, C, Java or other related languages.
• Experience with deep learning frameworks such as Pytorch or Tensorflow.
• Deep interest in cross-disciplinary communication towards conducting research in socio-technical systems and responsible AI.

• Intent to return to degree program after the completion of the internship/co-op.
• Proven track record of achieving significant results as demonstrated by grants, or fellowships, as well as publications in FAccT, AIES, *ACL.
• Contributions to affinity workshops at machine learning conferences (e.g. NeurIPS, ICML) welcome.
• Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches.
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Experience working and communicating cross functionally in a team environment.