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. Experience with development of Triton or CUDA kernels. Experience with distributed training and LLM infrastructure (e.g. Ray, TRL, vLLM, Triton, DeepSpeed, Unsloth, VeRL) and MLOps tooling (MLflow, Weights
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investigating how technology, space design, and pedagogy can together enable students to continue learning at work, in individual study, or in distributed settings following active, on-campus learning experiences
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and inference for distributed AI agents, and how the realities of networked operation shape the design of adaptive, resilient intelligence. Finally, the research will address how groups of embodied
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