Senior Solutions Architect – Higher Education and Research, AI, HP
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Job Description
Solutions Architect helping universities and research labs adopt NVIDIA AI and accelerated computing. Integrating GPU technologies into scientific research and advising academic partners.
Responsibilities:
- Partner with leading research labs, researchers, and university faculty as a trusted technical advisor
- Understand scientific goals and drive joint research projects at supercomputing scale
- Identify and accelerate high-impact workloads by integrating NVIDIA frameworks, libraries, and core software 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 and develop prototypical solutions addressing gaps between researcher needs and NVIDIA offerings
- 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 while using conferencing tools to support customers
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 a passionate learner
- Excellent organization skills for a heavily multi-tasked environment
- Fluent in English, both oral and written
- Comfortable working in Python
- Preferred: PhD in a STEM related discipline, with 3+ years of research in computational science combined with AI
- Preferred: Track record of high-impact publications and academic conference/workshop talks
- Preferred: Understanding of scientific policy engagement, grant processes, or national/European research program structures
- Preferred: Experience with NVIDIA's accelerated computing stack, CUDA, CUDA-X libraries, PhysicsNeMo, Warp, cuEquivariance, ALCHEMI, or Omniverse
Benefits:
- Diverse, supportive work environment
- Travel involved, with conferencing tools used to reduce time on the road
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