Research Scientist Intern, Language Generative AI

Research Scientist Intern, Language Generative AI 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 or develop methods and solutions for evaluations of models and 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. 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, C++, C, Java or other related languages. Experience building systems based on machine learning and/or deep learning methods. Preferred Qualifications 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, ICASSP, Interspeech 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, natural language processing, 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. Experience with deep learning frameworks.

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