Senior Solutions Architect, Higher Education and Research, Multimodal and Physical AI

NVIDIA, a pioneer in computer graphics and accelerated computing for three decades, is now shaping the AI era. The Senior Solutions Architect for Higher Education and Research, Multimodal and Physical AI will serve as the chief technical liaison for academic and research partners, helping them adopt NVIDIA’s cutting‑edge platforms. In this role you will work closely with leading university labs, faculty and researchers, learning their scientific objectives and co‑designing large‑scale projects that run on multi‑node GPU systems. You will embed NVIDIA’s frameworks, libraries and software stack into their workloads, support publications and conference talks, and deliver hands‑on trainings, workshops, lectures and demos across the full NVIDIA portfolio—including GPUs, CPUs, networking and software. Monitoring emerging research trends, you will translate gaps between user needs and NVIDIA offerings into prototype solutions and feed insights back to engineering. The position requires a graduate degree in a STEM field or comparable experience, plus at least five years of hands‑on work with multimodal and world‑model pipelines on multi‑node GPUs, covering data curation, pre‑training, post‑training, evaluation and efficient inference. Strong collaboration and communication abilities are essential, as is the capacity to explain complex concepts to both specialists and lay audiences. Fluency in English, both spoken and written, and proficiency in Python are mandatory. Candidates who hold a PhD with three or more years of research, a record of high‑impact publications or conference talks, and familiarity with NVIDIA’s visual and multimodal AI stack—such as CUDA‑X, Cosmos, NeMo, Megatron, Isaac, NuRec, TensorRT, NIM or MONAI—will stand out. The role involves about 20 % travel for face‑to‑face engagements, while the remainder relies heavily on conferencing tools, giving you flexibility to determine the best way to ensure customer success.