Senior Software Development Engineer in Test - NPI Bring-up SDET

NVIDIA•Santa Clara, CA
•$168,000 - $270,250

About The Position

The Senior Software Development Engineer in Test will join NVIDIA’s Compute CUDA Quality Assurance team and drive validation readiness for PCIe Data Center GPU programs. The role combines new silicon bring-up, CUDA and NVIDIA Driver quality, automation development, test infrastructure, and AI-assisted quality analysis. The team leads test planning, execution readiness, defect triage, and automation from early platform bring-up through key release stages. It collaborates across CUDA, NVIDIA Driver, GPU architecture, firmware, system platform, Quality Assurance, and program teams to translate feature requirements into measurable coverage, identify release risks, and drive issues to resolution.

Requirements

  • A BS or MS in Engineering, Computer Science, or a related field, or equivalent experience.
  • 8+ years of experience in software quality, test automation, or software development and validation.
  • Experience solving Linux and Windows system issues.
  • Development experience using scripting and programming languages such as Python, C, C++, CUDA, or Bash.
  • Experience debugging across hardware, firmware, operating system, driver, and application layers.
  • Knowledge of Quality Assurance methodology, risk-based test planning, functional validation, regression strategy, release readiness, CI/CD, API integrations, log analysis, root cause isolation, and defect triage.
  • Strong communication and teamwork skills, including the ability to explain release risk and clarify ownership, dependencies, and blockers.

Nice To Haves

  • Experience with NVIDIA GPU hardware, CUDA, PCIe-based data center GPUs, server platforms, CUDA C or C++ parallel programming, multiple GPU validation, P2P, reliability, or stress testing.
  • Experience developing scalable validation infrastructure for labs, cloud environments, containers, virtualization, or configuration management.
  • Practical use of AI-assisted analytics for test planning, automation, failure analysis, or defect detection.

Responsibilities

  • Develop CUDA Compute test plans and coordinate validation across PCIe high-performance computing GPUs, NVIDIA systems, OEM servers, GPU configurations, operating systems, driver modes, CUDA versions, and release stages.
  • Build test applications, automation frameworks, release configurations, and GitLab or Jenkins pipelines using Python, C, C++, CUDA, and Bash.
  • Convert NPI failures, customer defects, root cause findings, and suitable manual tests into reliable automated regression coverage.
  • Distinguish product regressions from automation, infrastructure, configuration, and intermittent issues.
  • Drive defects with clear reproduction steps, affected configurations, intended and actual results, supporting evidence, release impact, fix verification, and adjacent regression coverage.
  • Apply AI-assisted tools to analyze test runs and validate conclusions against source logs and engineering decisions.

Benefits

  • Equity
  • Benefits
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