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Meta is seeking Research Interns to join our Meta Superintelligence Lab in the post-training modeling team across language, and multimodal. 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, natural language processing, machine learning, and reinforcement learning. 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.
Job Responsibility:
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 to advance the science and technology of intelligent machines
Perform research that enables learning the semantics of and training generative models of data (images, video, 3D, text, audio, and other modalities)
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
Disseminate research results
When applicable, contribute to research that can be applied to Meta product development
Requirements:
Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or relevant technical field
Experience with Python, C++, C, Java or other related languages
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
Experience building systems based on machine learning and/or deep learning methods
Nice to have:
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, ACL, EMNLP, CVPR, ICCV, ECCV, 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
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
Experience in utilizing theoretical and empirical research to solve problems