Nvidia Solutions Architect - NVIDIA Cloud Partners 

United States, Texas 

65130830

What you'll be doing:

• Collaborating with NVIDIA Cloud Partners to create, implement, and put into operation NVIDIA's innovative hardware and software solutions.

• Partner with Sales Account Managers and other business leads to identify and secure business opportunities for NVIDIA products and solutions.

• Act as the primary technical support for customers during the development, construction and production of extensive GPU cloud infrastructure through whole customer lifecycle.

• Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions.

• Work with customers to build PoCs for solutions to address critical business needs by building out networking and compute infrastructure.

• Prepare and deliver technical content to customers including presentations, workshops, etc.

• Analyze and develop joint solutions for customer performance and scaling issues.

What we need to see:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

• Motivation and skills to own and drive technical engagements with customers throughout full customer life-cycle.

• 7+ 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 data center design, development and execution for AI and HPC.

• Efficient time management and capable of balancing multiple tasks. Ability to communicate ideas clearly through documents, presentations, etc.

Ways to stand out from the crowd:

• Practical familiarity with NVIDIA hardware (such as GPUs, ETH/IB networking components, storage, etc.) within extensive AI and HPC cluster settings.

• Practical knowledge of NVIDIA systems technology such as NCCL, DCGM, UFM, Mission Control, Base Command Manager, etc.

• Background with at scale GPU systems in general, encompassing performance testing, AI benchmarking, and more.

• Practical involvement in cluster administration and coordination (SLURM, K8s, etc.).