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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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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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research teams to install, port, optimize, benchmark, and tune scientific applications and toolsets. Support software environments for a wide range of computational workflows, including parallel and
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, enhanced sampling, QM/MM) Experience improving performance and scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation
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-performance computing environment, including multi-tenant compute, high-speed interconnects, and parallel filesystems Special Requirements: This position requires the ability to obtain and maintain a clearance
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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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in multiphysics modeling Experience in parallel programming on large-scale computational clusters Expertise in Matlab programming Active TS/SCI Clearance is preferred Special Requirement: This position
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, chunking, parallelization; Dask/Spark a plus). Experience using or building agentic/LLM-enabled workflows for data discovery, extraction, and normalization, with attention to provenance, reproducibility, and