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Tier-1 employer, metro location, and sought-after generative AI skills create moderate competition.
Deep LLM training, GPU cluster, and generative AI expertise limit cross-industry transferability.
Explicit 7+ years, advanced degree preference, and niche LLM/GPU requirements produce highly restrictive filters.
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Architect end-to-end generative AI solutions focused on Large Language Models (LLMs), including training, deployment, and Retrieval-Augmented Generation (RAG) workflows.
Collaborate with customers and partners to understand business challenges and design tailored AI solutions, leading workshops and design sessions.
Provide technical leadership by working closely with NVIDIA engineering teams to influence generative AI software evolution and optimize LLM training and inference on NVIDIA hardware.
Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
7+ years of technical experience in generative AI with strong emphasis on training and deploying Large Language Models.
Proven experience with LLM training and fine-tuning frameworks such as Megatron-LM, Megatron-Bridge, AutoModel, and PyTorch.
Expertise in GPU cluster architecture and model deployment/optimization with focus on GPU platforms.
Strong hands-on experience optimizing LLMs for production inference performance, memory, and resource efficiency.
Experience leading technical workshops and effectively communicating complex AI concepts to varied audiences.
Familiarity with cloud and on-premises deployment of LLMs, containerization (Docker), orchestration (Kubernetes), and GPU cluster management for scalable AI workflows.