Senior Solutions Architect, Higher Education, Research, AI, HPC
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Job Description
NVIDIA Solutions Architect advancing AI and HPC adoption across academia and research. Partnering with universities and labs on GPU-accelerated scientific workloads and joint research.
Responsibilities:
- Partner directly with leading research labs, researchers, and university faculty as a trusted technical advisor
- Understand customers' scientific goals and drive joint research projects at supercomputing scale
- Identify and accelerate high-impact workloads
- Integrate NVIDIA 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 and AI methods for scientific discovery
- Deliver hands-on trainings, workshops, lectures, and demonstrations across NVIDIA platforms
- Mentor power users to become NVIDIA champions
- Track emerging research trends
- Turn gaps between researcher needs and NVIDIA offerings into prototypical solutions
- Provide direct feedback to NVIDIA Engineering
- Maintain deep domain expertise across NVIDIA's GPUs, CPUs, networking, and software
- Travel for face-to-face customer meetings as needed
- Use conferencing tools to support customer success
Requirements:
- A graduate degree from a leading university in a STEM related discipline or equivalent experience
- 5+ years in the intersection of HPC and AI
- Experience running scientific workloads at scale on multi-node GPU systems
- Experience applying machine learning to scientific workloads
- Strong collaboration and communication skills
- Ability to build relationships with academic and research stakeholders
- Ability to communicate complex ideas clearly to expert and non-expert audiences
- Action oriented, analytical, self-motivated, and passionate learner
- Excellent organization skills for a heavily multi-tasked environment
- Fluent in English, both oral and written
- Comfortable working in Python
- Willingness to travel
- Preferred: PhD from a leading university in a STEM related discipline, with 3+ years of research in computational science in combination with AI
- Preferred: Track record of thought leadership, including high-impact publications and talks at academic conferences and workshops
- Preferred: Understanding of scientific policy engagement, grant processes, or national/European research program structures
- Preferred: Experience with NVIDIA's accelerated computing stack for science, powered by CUDA and CUDA-X libraries, e.g. PhysicsNeMo, Warp, cuEquivariance, ALCHEMI, Omniverse
Benefits:
- Diverse, supportive work environment
- Travel involved, but not life on the road
- Heavy use of conferencing tools
- Empowerment to determine how to get the job done
- Opportunity to work with leading research labs, researchers, and university faculty
- Mentorship and professional engagement through trainings, workshops, lectures, demonstrations, publications, conference presentations, and technical content
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