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Senior AI Performance Network Architect

NVIDIA· Architect
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Tel Aviv, YokneamFull-timePosted 4mo ago

About the role

AI Networking Architect role focusing on bridging AI workloads with data center infrastructure, driving AI workload optimization through analysis, simulation, and end-to-end systems thinking to influence NVIDIA’s networking and AI infrastructure roadmaps.

Responsibilities

  • Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.
  • Analyze new AI models, distributed training techniques, and inference workloads to understand their infrastructure requirements.
  • Build simulation and hardware platforms, run real AI workloads on them, and develop analytical tools to evaluate trade-offs across compute, memory, storage, and network behavior.
  • Translate research insights and workload behavior into actionable software, hardware, and networking architecture requirements.
  • Partner with architecture, software, and product teams to influence future NVIDIA networking and AI infrastructure roadmaps.
  • Drive architectural innovation by applying deep workload analysis to production machine learning frameworks.

Qualifications

  • B.Sc. or M.Sc. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
  • 5+ years of relevant industry or research experience. This is not an entry-level position; coursework and personal projects do not substitute for production or research experience at scale.
  • Hands-on experience running and analyzing AI workloads on multi-node systems — distributed training or large-scale inference.
  • Demonstrated performance analysis work: building analytical or simulation models of real systems, validating them against measurement, and identifying bottlenecks that led to design or deployment changes.
  • Strong systems-level thinking across the full AI stack, from model and framework behavior down through compute, memory, storage, and network.
  • Track record of translating research findings and workload analysis into concrete software and hardware specifications that engineering teams acted on.
  • Strong programming skills in Python and C/C++, applied to performance modeling, data analysis, and prototyping.

Skills

Required:PythonC/C++

Benefits

  • NVIDIA is committed to fostering a diverse work environment and is an equal-opportunity employer.
Last updated Oct 2, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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