NVIDIA seeks a Solutions Architect to bridge the gap between design and deployment of large-scale AI and HPC GPU infrastructure. You will drive end-to-end technology solution integration with NVIDIA's strategic customers and offer recommendations based on customer feedback within our diverse and supportive environment.
What You'll Do
- Collaborate with NVIDIA Cloud Partners to create, implement, and operate innovative hardware and software solutions.
- Partner with Sales Account Managers to identify and secure business opportunities for NVIDIA products.
- Act as the primary technical support for customers throughout the full lifecycle of extensive GPU cloud infrastructure development.
- Conduct regular technical customer meetings for project details, feature discussions, and debugging sessions.
- Work with customers to build Proofs of Concept (PoCs) addressing critical business needs by building networking and compute infrastructure.
- Prepare and deliver technical content including presentations and workshops.
- Analyze and develop joint solutions for customer performance and scaling issues.
What We're Looking For
- BS/MS/PhD in Mechanical/Electrical Engineering, or other Engineering fields, or equivalent experience.
- Motivation and skills to own and drive technical engagements with customers throughout the full lifecycle.
- 5+ years of Solution Engineering (or similar Sales Engineering, Cloud Engineering) experience working directly with partners and customers.
- Experience crafting and deploying large-scale cluster environments.
- Practical expertise in datacentre design, development, and execution for AI and HPC.
- Efficient time management and ability to balance multiple tasks.
- Ability to communicate ideas clearly through documents and presentations.
Nice to Have
- Practical familiarity with large datacentre design, power distribution, and cooling (liquid to chip).
- Practical familiarity with NVIDIA hardware (such as GPUs, ETH/IB networking components, storage) within extensive AI and HPC cluster settings.
- Background with at-scale GPU systems, encompassing performance testing and AI benchmarking.
Technical Stack
- GPUs
- ETH/IB networking components
- Storage
- AI and HPC cluster infrastructure
NVIDIA is an equal opportunity employer.
