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 sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, 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, C++, C, Java or other related languages. Experience building systems based on machine learning and/or deep learning methods. Intent to return to the 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 or similar. Experience working and communicating cross functionally in a team environment. Experience in advancing AI techniques, 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 with deep learning frameworks.