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supports unique research needs for the Department of Energy and other Government agencies with goals ranging from the integration of quantum computing in high performance computing architectures, improving
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with research programs in translating programmatic deliverables to baseline IT scope and architecture requirements. Major Duties/Responsibilities: Partnership Engagement: Manage a diverse portfolio of
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Computing to lead the design, implementation, and management of HPC systems within a classified environment. We are looking for candidates with extensive experience in HPC architecture, cluster management
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strategic management and strict adherence to security protocols. We are looking for candidates with extensive experience in either classified HPC data center operations, architecture, parallel computing
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workflows, including architectures and orchestration for AI agents operating across HPC, data, and experimental facilities, and the provenance, evaluation, and trustworthiness methods needed to run them
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environment. Preferred Qualifications: Experience with AI/ML approaches for spatiotemporal or Earth system data, including transformers, multimodal learning, representation learning, or related architectures
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, architecture/design implementation, testing, configuration management, and issues management. Collaborate with multidisciplinary engineering teams to translate system requirements into actionable software
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and
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technology remain secure. The team is collaborative and strives to ensure security practices and procedures are understood, implemented, and enforced. Major Duties/Responsibilities: System Design and Architecture
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architecture, and ORNL’s enterprise and high-performance computing (HPC) environments. The role is typically less about building individual models and more about designing, integrating, and governing end-to-end