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Senior Data Infrastructure Engineer, AI Performance

NVIDIA· Architect
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full-timePosted 1mo ago

About the role

Software engineer role focused on building and scaling the infrastructure for NVIDIA’s AI architecture simulation ecosystem, including distributed execution, data platforms, automation, and visualization to support large-scale design studies.

Responsibilities

  • Build scalable and reliable infrastructure for running large simulation studies across on-premises compute clusters and cloud environments, improving throughput, resource efficiency, and reproducibility.
  • Establish a unified storage and data platform as the source of truth for simulation configurations, execution state, results, and provenance.
  • Develop self-service analytics and visualization capabilities that help architects explore results and compare performance, power, and design trade-offs.
  • Partner with GPU architects, performance engineers, AI researchers, and software teams to translate emerging AI workloads into reusable simulation platform capabilities.
  • Help define the technical roadmap and engineering practices for NVIDIA’s next generation of AI architecture simulation platforms.

Qualifications

  • BS or higher degree in a relevant technical field (CS, EE, CE, Math, etc.).
  • 3+ years of experience building production infrastructure, distributed systems, or data platforms.
  • Strong software engineering and system-design skills in one or more programming languages, with a solid understanding of scalability, reliability, data consistency, and operational trade-offs.
  • Ability to work through ambiguous problems, simplify fragmented systems, and collaborate effectively across engineering and research teams.

Skills

Required:Distributed systems
Last updated Aug 28, 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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