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and well-tested software. Supporting the training, evaluation and deployment of large AI and foundation models across HPC, GPU and cloud environments. Establishing modern software-engineering practices
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software engineering and computational research practices, including version control, testing, documentation, reproducibility, and large-scale GPU or HPC environments. Preferred Industry or applied
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content before it is published. Research at the Center builds on the group's track record in data science, conversational AI, and marketing analytics and on substantial investments in on-premises GPU
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Working knowledge of GPU acceleration of computational workloads, preferably in a virtualized environment Working knowledge of KVM/QEMU virtualization, ContainerD or Docker container runtimes, and
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scientific software deployment, including MPI, GPU/accelerator technologies, Apptainer/Singularity containers, Conda environments, and research-oriented code libraries Advanced analytical skills to diagnose