Research Scientist Intern, GenAI Safety (PhD)

Meta is seeking Research Interns to join our Generative AI efforts. We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics.

Responsibilities

• Develop novel state-of-the-art generative AI algorithms and corresponding systems, leveraging various deep learning techniques.
• Help analyze and improve safety and robustness of corresponding deployed algorithms based on the project.
• Perform research to advance the science and technology of intelligent machines.
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
• Disseminate research results.
• Publish research results and contribute to research that can be applied to Meta product development.

Minimum Qualifications

• Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Computer Vision, Audio Processing, Artificial Intelligence, Generative AI, 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.
• Research experience in machine learning, deep learning, computer vision and/or natural language processing.
• Experience with Python, C++, C, Java or other related languages.
• Experience with deep learning frameworks such as Pytorch or Tensorflow.

Preferred Qualifications

• Intent to return to the degree program after the completion of the internship/co-op.
• Direct experience in privacy/ safety related research.
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences.
• Experience working and communicating cross functionally in a team environment.
• Publications or experience in machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science.
• Experience solving analytical problems using quantitative approaches.
• Experience setting up ML experiments and analyzing their results.
• Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories.