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tactile skins, and a dedicated GPU cluster with eight NVIDIA H200 GPUs alongside access to ETH's central compute and the Alps supercomputer at CSCS A multidisciplinary team of mechanical engineers
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or machine learning infrastructure, model deployment environments, or GPU-enabled systems. Familiarity with CI CD pipeline design and automation. Experience with hybrid infrastructure spanning on-premises and
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Process) Certifications/Licenses Required Knowledge, Skills, and Abilities Experience in GPU programming Experience working in interdisciplinary research teams Experience working with large and complex
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or High-Performance Computing clusters for GPU-intensive tasks. Desired: Masters degree in computer science, Data Science, Digital Humanities, or a related field. The College of the Arts and Sciences
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benchmark them with a realistic case study. The main focus of the project can develop either more in the mathematical theory of MCMC, the implementation of code for the Jülich supercomputers (GPU/CPU
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substantial investments in on-premises GPU infrastructure that allows us to work with confidential partner data under full data control. The focus of the position is on research, aiming at publications in
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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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infrastructure, including high-performance/GPU compute, research data storage, and collaboration with UT Austin's central research computing resources such as TACC, with clear separation between research and
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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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. This position will work within Research Computing to architect advanced computing, GPU-enabled environments and serve as a specialized partner to researchers to develop AI/ML research workflows within UAB