Research Scientist Intern, Monetization Computer Vision (PhD)

Research Intern

Meta is seeking Research Interns to join the Monetization Generative AI team. The team is dedicated to advancing the field of generative AI through fundamental advancements in technologies to interact with and understand the world. Interns will have the opportunity to make core algorithmic advances and apply these ideas at an unprecedented scale.

Responsibilities

• Conduct research to advance the science and technology of generative AI.
• Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities).
• Collaborate with researchers and cross-functional partners, including communicating research plans, progress, and results.
• Devise data-driven models of image generation and text generation.
• 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, Artificial Intelligence, or relevant technical field.
• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
• Experience in C, C++, Python, Java, or other related programming language.
• Experience building systems based on machine learning and/or deep learning methods.

Preferred Qualifications

• 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, fellowships, patents, as well as publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, and ACL.
• Experience with Generative AI, including diffusion models and LLM's.
• Background in advancing AI techniques in computer vision, including core contributions to open source libraries and frameworks in computer vision.
• 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.
• Experience in utilizing theoretical and empirical research to solve problems.
• Experience working and communicating cross-functionally in a team environment.