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Field
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: Ability to work with large structured and unstructured datasets, and GPU-accelerated computing. Proven experience with Large Language Models. Required Skill/Ability 3: Sound background in theoretical and
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computer science or a science or engineering field. Expertise working with high-performance computing systems, GPU programming, machine learning, and/or full-stack. Experience teaching best practices in software
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well as the newly launched Center for Generative AI and its associated GPU cluster consisting of 600 GH200 nodes. Qualifications All candidates must hold a Ph.D. or equivalent degree in Chemistry, Molecular Biology
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challenge the status quo. At Jane Street, you will work alongside a tight-knit team, utilizing petabytes of data, our computing cluster with hundreds of thousands of cores, and our growing GPU cluster
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learning, AI engineering, AI infrastructure, hybrid cloud computing, and parallel programming with GPUs, to work at the Institute for Artificial Intelligence and Data Science (IAD). As a Senior Research
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, hybrid cloud computing, and parallel programming with GPUs. As a Junior Research Engineer, you should have some basic understanding and experience in the development of scalable AI systems and deployment
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that combine parallel architectures (i.e., GPUs or accelerator boards, clusters) and numerical algorithms suited to such architectures with the goal of improving the speed of convergence and the stability
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for the Foundations of Machine Learning (IFML), and Good Systems initiative as well as the newly launched Center for Generative AI and its associated GPU cluster consisting of 600 GH200 nodes. All positions are subject
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conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings. Knowledge of systems
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
of data scientists/clinicians and working with unique datasets from multiple academic medical centers (e.g. UNC, UCSF, Mayo Clinic, Memorial Sloan Kettering, etc). Lab dedicated GPU workstations/servers and