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of unparalleled computing resources in the academic environment by optimizing AI/ML models including scaling models across a large set of GPUs; building or optimizing LLMs to tackle new, complex tasks; developing
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computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI environments and tools. Prior experience
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support. Deep understanding of modern machine learning architectures and optimization techniques. Proficiency in deep learning frameworks (PyTorch). Experience with Nvidia GPU stack and HPC technologies
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