Solutions Architect - AI Technology Center, Foundation Model Building

소개

NVIDIA AI Technology Center is seeking outstanding Senior Solutions Architects to catalyze the global research community by embedding NVIDIA as a core scientific collaborator. We move beyond standard technical support to act as elite research partners, driving the adoption of NVIDIA's platform through high-impact, co-authored breakthroughs and the shared pursuit of frontier AI discoveries. Primary focus on building foundation model engagements with researchers and developers at our key partner researcher from universities and joint labs.

주요업무

• Create fruitful technical engagements with top developers and influential researchers from the universities or enterprises building foundation models in Korea and lead strategic relationships with them. • Help them develop AI models more efficiently by proposing state-of-the-art training and optimization frameworks including Megatron-LM, Megatron-Bridge, NeMo-RL, or TensorRT-LLM. • Promote the results of the collaboration between NVIDIA and those teams with the support of marketing teams by publishing press releases and celebrate together by presenting them at GTC. • Advise on the transition from experimental code to large-scale, production-ready research environments, demonstrating the performance leap provided by the NVIDIA technology stack.

자격요건

• PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) • Proven experience in managing complex technical projects and navigating corporate strategic goals • 5+ year hands-on experience in full AI model lifecycle, including pre-training, supervised fine-tuning, post-training such as reinforcement learning, optimization, and evaluation. • Experience with NVIDIA GPUs and software libraries • Strong problem-solving and debugging skills • Excellent presentation, communication, and collaboration skills • Strong written and oral communication skills in English.

우대사항

• Good track record of academic research publications • Experience working across academia, industry and the government • Understanding of infrastructure factors that can affect AI model development such as GPU architecture, server block diagram, or networking bandwidth among GPU servers or between GPU servers and shared storage.

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