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Field
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-throughput processing. Enhance the computational efficiency of compute environments by optimizing resource allocation (including CPU/GPU utilization), parallelizing data pipelines, and resolving processing
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Intelligence, Machine Learning, Data Science, Security and Privacy, Parallel and Distributed Computing, Deep Learning, Internet of Things (IoT), and Algorithms. Successful candidates will hold a joint
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software in high-performance computing (HPC) environments. Experience with parallel and accelerated computing frameworks (e.g., OpenMP, MPI) and familiarity with GPUs and large-scale storage systems. Strong
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Language Models (LLMs). Distributed Machine Learning: Specialization in data parallelism, model-parallelism, and collective communication strategies in large-scale environments. Proficiency in frameworks
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video. You will lead the architecture and development of distributed systems that manage and serve massive datasets—including over 100 million media assets in the Macaulay Library—and support the full
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for new hires Phone list maintenance and OIT billing review Email distribution list administration Planning and coordination of departmental events Calendar and scheduling support for administrative
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. Demonstrated programming ability and knowledge of Python and/or C++. Experience with deep learning frameworks like PyTorch and application on high-performance computing (HPC) environments using distributed data
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for Science @ Scale: Pretraining, instruction tuning, continued pretraining, Mixture-of-Experts; distributed training/inference (FSDP, DeepSpeed, Megatron-LM, tensor/sequence parallelism); scalable evaluation
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management of High-Performance Computing (HPC) systems within a classified environment. We are looking for candidates with experience in HPC architecture, cluster management, and parallel computing, with a
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software on HPC systems. Familiarity with performance analysis and compiler optimization techniques. Experience with distributed and parallel computing technologies such as MPI and OpenMP. Experience with