NVIDIA is looking for an experienced systems and network infrastructure Solutions Architect. Do you want to be part of a team that brings new Artificial Intelligence (AI) hardware and software technologies to production in the field? We are looking for a compute and networking savvy Solution Architect to join the NVIDIA Solution Architecture Engineering (SA) team focused on supporting accelerated computing applications.
As part of the NVIDIA SA organization, you will be driving our end-to-end technology solutions integration with some of NVIDIA's most strategic technology customers, as well as offering recommendations to business and engineering teams on our product technology.
What You'll Be Doing:
Working with NVIDIA Consumer Internet and IT Services customers on data center GPU server and networking infrastructure deployments as solution architect. Guide customer discussions on network topologies, compute/storage and support bring up of server/network/cluster deployments. You will need to visit customer data center during bring up phase.
Identifying new project opportunities for NVIDIA products and technology solutions in data center and artificial intelligence applications. Work closely with the Systems/Network Engineering, Product management and Sales teams
Work as customer trusted advisor conducting regular technical customer meetings for product roadmap, cluster debug, feature discussions and introduction to new technology solutions
Building custom product demonstrations and POCs for solutions that address critical business needs of our customers
Analyzing and debugging compute/network performance issues
What We Need To See:
BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.
This role is for an individual with the motivation and skills to drive the data center engagements. Ideal candidate has 6+ years of Solution Engineering (or similar Engineering roles) experience
System level understanding of server architecture, NICs, Linux, system software and kernel drivers
Practical knowledge of Networking - switching & routing for Ethernet/Infiniband, and Data Center infrastructure (power/cooling)
Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes is a plus
Effective time management and capable of balancing multiple tasks
Ability to communicate your ideas/code clearly through documents, presentation etc
Ways To Stand Out From The Crowd:
External customer facing skill set and background
Experience with bring up 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 systems/SDKs (e.g. CUDA), NVIDIA Networking technologies (e.g., DPU, RoCE, InfiniBand), and/or ARM CPU solutions
Familiarity with virtualization technology concepts
We make extensive use of conferencing tools, but occasional (20%) travel is required for on-site visit to customers and industry events. We are open to remote work location and look forward to have you join our team!
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
