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Field
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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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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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computing and GPU infrastructure for the development and evaluation of LLM-, VLM-, and agentic AI solutions Research across the entire automotive software development lifecycle, from requirements and software
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streams with perturbation signatures and fit these. For these fits, we will explore the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use
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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
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, validation, calibration, and inference. Working with large, longitudinal, structured and unstructured datasets in Linux and high-performance or GPU-accelerated computing environments. Applying rigorous methods
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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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science, conversational AI, and marketing analytics and on substantial investments in on-premises GPU infrastructure that allows us to work with confidential partner data under full data control. The focus
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distributed training concepts, GPU-based training, checkpointing, experiment tracking, training stability and compute optimisation. MLOps, infrastructure and deployment: Familiarity with Linux environments