Senior Solutions Architect, AI Infrastructure

NVIDIA is looking for an experienced GPU and network systems Solutions Architect & Engineer. You will be part of a team that brings new Artificial Intelligence (AI) hardware and software technologies to production in customer data centers.

As part of the NVIDIA SA organization, you will drive deployment of end-to-end technology solutions integration at some of NVIDIA's most strategic technology customers. You will also offer recommendations to business and engineering teams on the product roadmap.

Responsibilities:

• Work with NVIDIA AI Native and Consumer Internet customers on large data center GPU server and networking system deployments as Solution Architect Engineer.
• Guide customer discussions on network design, compute/storage, and support bring up of server/network/cluster deployments.
• Visit customer data centers during the bring-up phase.
• Demonstrate subject matter expertise in advanced GPU & network systems and be a trusted technical advisor to NVIDIA's strategic customers.
• Bring customer-specific requirements to product teams to guide product roadmap features.
• Identify new project opportunities for NVIDIA products and technology solutions in data center and artificial intelligence applications.
• Work closely with the GPU/Network Systems Engineering, Product management, and Sales teams.
• Conduct regular technical customer meetings for product roadmap, cluster issues debug, feature discussions, and introduction to new technology solutions.
• Build custom product demonstrations and POCs for solutions that address critical business needs of customers.
• Analyze and debug compute/network configuration, performance issues to deliver performant clusters.

Requirements:

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.
• 6+ years of Systems/Solution Engineering (or similar Engineering roles) experience.
• System-level expertise of CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers.
• Experience with networking switches for Ethernet/Infiniband, and Data Center infrastructure (power/cooling).
• Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes.
• Effective time management and capable of balancing multiple tasks.
• Strong verbal/written communication skills and share ideas/code clearly through documents, presentations, etc.

Benefits:

• Equity
• Benefits

Optional Requirements:

• External customer-facing background
• Experience with bringup and deployment of large clusters
• Systems engineering, coding, and debugging skills including experience with C/C++, Linux kernel, and drivers
• Hands-on experience with NVIDIA GPU systems/SDKs (e.g., CUDA), NVIDIA Networking technologies (e.g., NICs, RoCE, InfiniBand), and/or ARM CPU solutions
• Familiarity with virtualization technology concepts