Solutions Architect, Higher Education and Research
NVIDIA
Job Overview
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Job Description
About the Role
The Solutions Architect, Higher Education and Research at NVIDIA works with customers in universities and research institutions. This role focuses on engaging academic customers with NVIDIA's advanced platforms for machine learning, deep learning, data science, and HPC.
Key Responsibilities
- Lead HPC and AI technical engagements with academic customers.
- Understand customer goals and technical needs to deliver innovative solutions.
- Develop training materials, whitepapers, blogs, and technical documentation.
- Provide customer requirements to engineering for product improvements.
- Utilize conferencing tools and travel up to 20% as required.
Required Qualifications
- BS, MS or PhD in Engineering, Mathematics, Physical Sciences, or Computer Science (or equivalent experience).
- 5+ years of relevant work experience with HPC, deep learning and GPU technologies.
- Proven ability to port and optimize scientific applications for GPUs.
- Strong programming, problem-solving, and debugging skills.
- Excellent presentation, communication, and collaboration skills.
Preferred Skills & Standout Qualifications
- Experience working with academic research communities supporting HPC or AI.
- Full-stack scientific computing including parallel programming in C/C++, Python, CUDA, etc.
- Experience with orchestration and containerization tools like Slurm, Kubernetes, Docker.
Additional Information
This role offers a competitive base salary that varies by level and experience, eligibility for equity and benefits, and uses NVIDIA's innovative AI tools in the recruiting process. Applications are open until January 13, 2026. NVIDIA is committed to diversity and is an equal opportunity employer.
Key skills/competency
- HPC
- AI
- GPU
- Deep Learning
- Scientific Computing
- Programming
- Customer Engagement
- Training
- Communication
- Collaboration
How to Get Hired at NVIDIA
- Research NVIDIA's culture: Understand their mission and recent innovations.
- Customize your resume: Tailor it to demonstrate HPC and AI skills.
- Highlight technical projects: Showcase experience with GPUs and deep learning.
- Prepare for interviews: Review customer engagement and technical troubleshooting cases.
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