Solutions Architect, Networking

🕒 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

• Becoming the trusted technical advisor for NVIDIA Cloud Partners in Canada to rapidly bring NVIDIA Data Center GPU and networking platforms to market at scale • Collaborating directly with customers to build, deploy, and optimize large-scale AI training and inference infrastructure using NVIDIA technology • Analyzing deployment and performance data, identifying product health trends, system bottlenecks, and operational risks • Solving challenging technical problems involving GPUs, networking, drivers, containers, firmware, and distributed system interactions • Delivering streamlined executive-level communication on status, risks, progress, and required decisions • Some travel to customer sites is required, up to 20%

🎯 Requirements

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) • 5+ years of Solution Architecture (or similar Sales Engineering, Systems Engineering, Cloud Engineering, Solution Engineering) • Understanding of high-performance networking technologies (e.g., RDMA, congestion control, high-bandwidth interconnects) • Hands-on experience with large-scale NVIDIA GPU platforms, including multi-GPU and multi-node architectures • Familiarity with NVIDIA system software stacks: CUDA, NCCL, NVSwitch/NVLink, driver behavior, and performance tuning • Strong Linux fundamentals across drivers, kernel subsystems, cgroups, containers, and node-level performance analysis • Excellent presentation, communication, and collaboration skills

🏖️ Benefits

• Highly competitive salaries • Comprehensive benefits package • Eligibility for equity