Senior Solutions Architect, Supercomputing
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Job Description
NVIDIA Solutions Architect advancing GPU, HPC, and AI platforms for enterprise customers. Advising partners, leading technical engagements, and integrating CUDA, networking, and modern AI architectures.
Responsibilities:
- Engage with customers, partners, and NVIDIA software engineers to collaborate with developers and support applications and platforms leveraging NVIDIA technology
- Partner with industry and account teams in a customer-facing role to understand customer goals, strategies, and technical needs
- Help define and deliver high-value solutions meeting customer needs
- Document knowledge and teach others through targeted samples, white papers, blogs, wiki articles, and customer problem-solving sessions
- Lead integration of NVIDIA technology into AI workloads and workflows, HPC, and enterprise GPU and networking architectures for datacenter and edge applications
- Strategically partner with lighthouse customers and industry-specific solution partners targeting NVIDIA’s computing platform
- Educate customers through product roadmaps, presentations, briefings, and hands-on developer engagement
- Serve as a trusted technical advisor and leader to partners, customers, and the Solutions Architect team
- Travel as needed to support partners and customers
Requirements:
- This position requires a security clearance and U.S. citizenship
- Bachelors degree in Engineering, Mathematics, Physics, Computer Science or equivalent experience
- 8+ years of work-related experience in data science or software development with knowledge of parallel computing with GPUs
- Background working with modern application deployment practices including Slurm, Docker/Containers, and Kubernetes
- Experience with modern Generative AI and Agentic AI architecture and frameworks
- Strong written and oral communication skills
- Experience supporting customers/partners in technical engagements
- Strong organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects
- Strong analytical and problem-solving skills
- Experience applying data science to industry problems
- Experience using GPGPU programming and design practices
- CUDA programming and optimization experience
- Experience with network software development
- Published record of thought leadership in a technical area or industry segment, including Deep Neural Network, Machine Learning R&D, Agentic AI, surrogate Models, or foundation models
Benefits:
- Equity
- Benefits
- Some travel is required for this role
- Flexible/empowered work approach to find the best way to get the job done
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