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

NVIDIA is looking for a Senior Solutions Architect to work with academia and research partners. The successful candidate will be a primary technical contact for customers, engaging deeply with researchers and application developers to drive the adoption of NVIDIA technology.

Key Responsibilities:

• Partner with leading research labs, researchers, and university faculty as a trusted technical advisor
• Develop a keen understanding of their scientific goals and drive joint research projects at supercomputing scale
• Identify and accelerate high-impact workloads by integrating NVIDIA's frameworks, libraries, and core software stack into research projects
• Help researchers amplify their impact through publications, conference presentations, and technical content
• Advocate for accelerated computing, robotics, Multimodal AI and Physical AI, and deliver hands-on trainings, workshops, lectures and demonstrations across NVIDIA's platforms
• Mentor power users to become NVIDIA champions
• Track emerging research trends and turn gaps between researcher needs and NVIDIA's offerings into prototypical solutions and direct feedback to NVIDIA Engineering
• Maintain deep expertise in your domain while staying versatile across NVIDIA's full platform: GPUs, CPUs, networking, and software

Requirements:

• A graduate degree from a leading university in a STEM related discipline or equivalent experience
• 5+ years across the multimodal and world model lifecycle on multi-node GPU systems
• Strong collaboration and communication skills, with the ability to build relationships with academic and research stakeholders
• Action oriented, analytical, self-motivated, and a passionate learner, with excellent organization skills to work in a heavily multi-tasked environment
• Fluent in English, both oral and written, and comfortable working in Python

Nice to Have:

• A PhD from a leading university in a STEM related discipline, with 3+ years of research in the domain
• A track record of thought leadership: high-impact publications, talks at academic conferences and workshops, as well as good understanding of scientific policy engagement, grant processes, or national/European research program structures
• Experience with NVIDIA's stack for visual and multimodal AI, built on CUDA and CUDA-X