Solutions Architect, AI Infrastructure

🕒 May 11

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Working with NVIDIA Cloud Partners in Canada on large data center GPU server deployments • Guide customer discussions on network design, compute/storage, and support bring up of server/network/cluster deployments • Visit customer data center during bring up phase • Become the primary technical driver for customers during design, development, construction, integration, and production of GPU Cloud infrastructure • Conduct regular technical customer meetings for product roadmap, cluster issue debugging, feature discussions, and introduction to new technology solutions • Partner with other SAs, Account Managers, Engineering, and Product leaders to secure business opportunities

🎯 Requirements

• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or other Engineering fields or equivalent experience • 5+ years of Solution Engineering (or similar Sales Engineering, Cloud Engineering, Solution Architecture) including experience working directly with partners and customers • 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 and Kubernetes • Excellent presentation and communication skills • Self-starter with a passion for growth, continuous learning, and sharing insights

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development • Bonuses • Stock options