Guide customers through the end-to-end process of AI adoption—from requirements gathering and proof-of-concept development to deployment, integration, benchmarking and ongoing optimization * Background with accelerating scientific algorithms using parallel programming (e.g., using CUDA), or experience with distributed programming models for supercomputing applications, AI deployment/inference technologies (e.g. TensorRT), cloud deployment (AWS, Azure) or optimization frameworks (e.g. cuOpt), is a plus.
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