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training, fine-tuning, evaluation, and experimentation. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background
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. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background in database systems, including: Relational databases (e.g
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computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background in database systems, including: Relational databases (e.g., PostgreSQL / SQL) Graph databases
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), including model training, evaluation, and experimentation. Familiarity with distributed or accelerated computing environments (e.g., GPU‑enabled systems, shared compute clusters). Working knowledge
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, evaluation, and experimentation. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background in database systems
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projects Preferred: Experience with educational technology development and web programming LAMP stack design and implementation experience Knowledge of GPU and FPGA cluster management Experience with federal
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programming LAMP stack design and implementation experience Knowledge of GPU and FPGA cluster management Experience with federal research compliance and security requirements Background in AI/ML computing