Research Scientist Intern, Computer Vision for Generative AI (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 Interns to join our Generative AI efforts across modalities (images, video, 3D, audio, etc.) . 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 generative modeling, deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.Research Scientist Intern, Computer Vision for Generative AI (PhD) Responsibilities

• Develop novel state-of-the-art generative AI algorithms and corresponding systems, leveraging various deep learning techniques.
• Based on the project, help analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
• Perform research that enables learning the semantics of and training generative models of data (images, video, 3D, text, audio, and other modalities).
• Conduct research to enhance the efficiency and effectiveness of diffusion models for both image and video applications.
• Explore and develop methods for real-time inference of diffusion models.
• Share and publish research findings to contribute to the broader scientific community.

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.
• Experience with Python or other related 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 first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP or similar.
• Experience working and communicating cross functionally in a team environment.
• Experience 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 analyze 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 with deep learning frameworks.

LocationsAbout Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.


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