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Senior Software QA Test Development Engineer - Diagnostics

NVIDIA· Engineer, SW QA Test Dev
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Santa Clara, CA$140k - $270.3kfull-timePosted 2mo ago

About the role

QA test development engineer focused on NVIDIA HGX/DGX/MGX platform testing, reliability, and automation across servers, OS, firmware, and CUDA SW stack, with emphasis on AI tools/NLP, DevOps, and CI/CD in a Linux/server environment.

Responsibilities

  • Responsible for the development and execution of NVIDIA HGX/DGX/MGX platform test plan on servers, OS, FW and CUDA SW stack from design doc.
  • Installing and testing various systems OS, server firmware and SW stack.
  • Drive support for root cause analysis on reliability and validation test failures to identify root cause(s) and achieve mitigation.
  • Build, develop/debug server and OS level automation front-end and back-end framework and tests
  • Review partner and supplier test results and prescribe additional reliability testing on components, servers, and packaging as needed.
  • Work in an agile software development team with very high production quality standards.
  • Manage bug lifecycle and collaborate with inter-groups to drive for solutions.

Qualifications

  • Bachelor’s Degree (or equivalent experience) in a STEM field
  • 5+ years proven experience; or master’s degree.
  • Proven years of OS and server level automation, CI/CD process and DevOps experience using Python, SHELL, Ansible, Jenkins, C/C++, Java, JavaScript
  • Strong server and Linux troubleshooting and debugging experience in a bare-metal and KVM/VMWare/Hyper-V environment.
  • Good knowledge and hands-on experience in model testing, AI tools/frameworks (TensorFlow, Pytorch, Cursor and etc…), NLP and LLM benchmarking
  • Experience in using AI development tools for test plans creation, test cases development and test cases automation
  • Strong experience in FW, BMC/OpenBMC, Network protocol, internal/external enterprise storage devices, PCIe buses and devices, IO sub-devices, CPU and memory, ACPI, UEFI spec, Redfish
  • Proven years of experience in GitHub/Gitlab/Gerrit, PXE, SLURM, Stack/Kubernetes/Docker)
  • AI related tools, LLM and NLP experience (stand-out).
  • Experience with NVIDIA GPU hardware and virtualization in Linux (KVM, Docker/Kubernetes) and CUDA/OpenCL background (nice to have)

Skills

Required:OS and server automationCI/CDProgramming languagesLinux troubleshootingAI tools & frameworks
Nice to have:Virtualization environments

Benefits

  • equity
  • benefits (as per NVIDIA benefits)
Last updated Sep 18, 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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