Solutions Architect, Networking
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Job Description
Solutions Architect designing and deploying NVIDIA GPU networking infrastructure for Canadian cloud partners. Optimizing large-scale AI training and inference systems across customer environments.
Responsibilities:
- Become the trusted technical advisor for NVIDIA Cloud Partners in Canada to bring NVIDIA Data Center GPU and networking platforms to market at scale
- Collaborate directly with customers to build, deploy, and optimize large-scale AI training and inference infrastructure using NVIDIA technology
- Analyze deployment and performance data, identifying product health trends, system bottlenecks, and operational risks
- Solve technical problems involving GPUs, networking, drivers, containers, firmware, and distributed system interactions
- Deliver executive-level communication on status, risks, progress, and required decisions
- Collaborate with internal engineering, product, and business teams on performance analysis and modeling of large GPU clusters
- Travel to customer sites and industry events occasionally, 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, or Solution Engineering experience
- Understanding of high-performance networking technologies, including RDMA, congestion control, and high-bandwidth interconnects
- Hands-on experience bringing up and validating large-scale NVIDIA GPU platforms, including multi-GPU and multi-node architectures
- Familiarity with NVIDIA system software stacks, including CUDA, NCCL, NVSwitch/NVLink, driver behavior, and performance tuning
- Ability to identify performance bottlenecks at the cluster, node, accelerator, network, or application layer
- Strong Linux fundamentals across drivers, kernel subsystems, cgroups, containers, and node-level performance analysis
- Excellent presentation, communication, and collaboration skills
- Prior experience deploying or optimizing deep learning training and inference at scale in production environments is advantageous
- Familiarity with NVIDIA hardware and systems technology such as GPUs, networking, storage, NCCL, DCGM, UFM, Mission Control, and Base Command Manager is advantageous
- Demonstrated leadership resolving multi-team infrastructure challenges is advantageous
- Record of taking GPU or infrastructure products from pilot to high-volume deployment is advantageous
- Ability to travel to customer sites and industry events occasionally, up to 20%
Benefits:
- Highly competitive salaries
- Comprehensive benefits package
- Equity
- Benefits for employees and families
- Remote work arrangement
- Occasional travel to customer sites and industry events
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