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Position Details Position Information Recruitment/Posting Title Lead Software Developer – GPU-accelerated Free Energy Simulation and Machine Learning Methods Department Quantitative Biomedicine Inst
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, deployment, modernization, and evolution of secure HPC environments supporting classified national security and scientific missions. Architect scalable compute solutions integrating CPU/GPU resources, high
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, and other central IT teams on shared services and infrastructure. The position also supports the network and physical hardware infrastructure for research computing, including HPC, GPU-accelerated
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GPU platforms support machine learning training and inference, including models served through NVIDIA Triton and large language models hosted on facility hardware. The Lab has also built an agentic AI
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(e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative
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AI Gateway, API Management, model-serving environments, and local GPU compute resources. This position supports reliable AI service delivery, local model life cycle management, and operational
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. Oversee the operation, monitoring, security, performance, and lifecycle management of enterprise AI platform services, including AI gateways, approved model access, model routing, and local GPU-enabled
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, automating, and optimizing the GPU and AI and computing infrastructure used by researchers across the university, along with the high-performance computing systems that support it. This position will be filled
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, automating, and optimizing the GPU and AI and computing infrastructure used by researchers across the university, along with the high-performance computing systems that support it. The position will be filled
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systems, including GPU-accelerated platforms. Develop and maintain scientific software, primarily in Python, using modern practices for software development, testing, documentation, and version control