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.