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

NVIDIA, a pioneer in graphics and accelerated computing for three decades, is expanding AI's reach into higher‑education and research. The Senior Solutions Architect will act as the chief technical liaison for universities and research institutes, helping them harness NVIDIA's multimodal and physical AI platforms to push scientific frontiers. In this role you will partner directly with leading labs, faculty and researchers, learning their scientific objectives and co‑designing large‑scale projects 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 and demos. Monitoring emerging research trends, you will translate gaps into prototype solutions and feed insights back to NVIDIA engineering while staying proficient across GPUs, CPUs, networking and the full software suite. The position requires a graduate degree in a STEM discipline (or comparable experience) and at least five years of hands‑on work with multimodal AI and world‑model pipelines on multi‑node GPU clusters, covering data curation, pre‑training, evaluation and efficient inference. Strong collaboration and communication abilities are essential to build relationships with academic stakeholders and explain complex concepts to both experts and novices. The candidate must be action‑oriented, analytical, self‑driven, and organized enough to juggle multiple tasks, fluent in spoken and written English, and comfortable coding in Python. Travel makes up roughly one‑fifth of the working time, with the remainder performed remotely using conferencing tools. Preferred qualifications include a PhD in a STEM field and three or more years of research experience in the domain, a proven record of high‑impact publications and conference presentations, and familiarity with scientific policy, grant mechanisms and European research programme structures. Experience with NVIDIA's visual and multimodal AI stack, CUDA, CUDA‑X, Cosmos, NeMo, Megatron, Nemotron, Isaac, NuRec, TensorRT, NIM and domain frameworks such as MONAI, is considered a strong advantage. What the role asks for: - Graduate degree in STEM or equivalent experience - 5+ years multimodal AI lifecycle on multi‑node GPUs - Strong collaboration and communication skills - Fluent English oral and written - Comfortable working in Python - Travel 20 % of working time - PhD in STEM (nice‑to‑have) - 3+ years research in domain (nice‑to‑have) - High‑impact publications and conference talks (nice‑to‑have) - Knowledge of scientific policy and grant processes (nice‑to‑have) - Experience with NVIDIA CUDA‑X, Cosmos, NeMo, Megatron (nice‑to‑have) - Familiarity with Isaac, NuRec, TensorRT, NIM, MONAI (nice‑to‑have)