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scalable compute solutions integrating CPU/GPU resources, high-speed interconnects, parallel storage, scheduling, and supporting infrastructure. Establish technical standards, architectures, and engineering
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and developing sustainable engineering solutions. Evaluate and introduce emerging technologies, architectures, and engineering approaches, including HPC, AI/ML, GPU computing, containers, and other
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compute (CPU/GPU), high-speed interconnects, storage and parallel file systems, cluster management, and user-facing platform services. In practice, the Senior HPC Architect drives end-to-end technical
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software (e.g., Paraview). Preferred Qualifications: Exposure to developing agentic workflows. Code development using Git repositories, GPU computing. Development of agentic workflows for scientific
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, Ansible, or similar technologies. Experience with Git-based development workflows, CI/CD, infrastructure-as-code, or modern DevOps practices. Experience designing infrastructure supporting HPC, AI/ML, GPU
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documentation of HPC architectures, configurations, and operational procedures. Guide the architecture of the next-generation of GPUs through an intuitive and comprehensive grasp of how GPU architecture affects
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, or other highly regulated computing environments. HPC, AI/ML infrastructure, GPU computing, containers, Kubernetes, or advanced computing platforms. Infrastructure-as-code, advanced automation, CI/CD
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or OpenMP. Experience in heterogeneous programming (i.e., GPU programming) and/or developing, debugging, and profiling massively parallel codes. Experience with using high performance computing for lattice
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preferred). Familiarity with CUDA toolchains and building GPU-enabled software. Experience with automation/configuration management tools (e.g., Ansible, Puppet, or similar). Experience developing tools
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managing systems utilizing GPU (NVIDIA and AMD) clusters for AI/ML and/or image processing. Knowledge of networking fundamentals including TCP/IP, traffic analysis, common protocols, and network diagnostics