Senior Software QA Test Development Engineer - Diagnostics

at Nvidia
USD 140,000-270,200 per year
SENIOR
✅ On-site

Tech Stack

AI @ 4 Agile Ansible @ 4 CI/CD @ 4 CUDA @ 6 Debugging @ 7 DevOps @ 4 Docker @ 1 GPU @ 4 GitHub @ 1 Java @ 4 JavaScript @ 4 Jenkins @ 4 Kubernetes @ 1 LLM @ 4 Linux @ 7 Mathematics @ 4 NLP @ 4 OpenCL @ 6 Parallel Programming @ 6 PyTorch @ 4 Python @ 4 Slurm @ 1 Software Development @ 4 TensorFlow @ 4

Details

NVIDIA is looking for an experienced software quality assurance engineer to join its platform SWQA team. The role focuses on enterprise server integration, Linux, reliability testing, telemetry, scale-out clusters, test-plan development, AI tools, NLP, DevOps, and CI/CD. The position supports NVIDIA HGX, DGX, and MGX platforms across servers, operating systems, firmware, and the CUDA software stack.

Responsibilities

  • Develop and execute platform test plans for NVIDIA HGX, DGX, and MGX platforms, including servers, operating systems, firmware, and the CUDA software stack.
  • Install and test operating systems, server firmware, and software stacks.
  • Support root-cause analysis of reliability and validation test failures and drive mitigation.
  • Build, develop, and debug server- and operating-system-level automation frameworks and tests, including front-end and back-end components.
  • Review partner and supplier test results and prescribe additional reliability testing for components, servers, and packaging as needed.
  • Work in an agile software development team with high production-quality standards.
  • Manage the bug lifecycle and collaborate across groups to drive solutions.

Requirements

  • Bachelor's degree, or equivalent experience, in a STEM field such as science, technology, engineering, mathematics, or physics.
  • Five or more years of proven experience, or a master's degree.
  • Experience with operating-system and server-level automation, CI/CD processes, and DevOps using Python, Shell, Ansible, Jenkins, C/C++, Java, and JavaScript.
  • Strong server and Linux troubleshooting and debugging experience in bare-metal and KVM, VMware, or Hyper-V environments.
  • Knowledge of and hands-on experience with model testing, AI tools and frameworks such as TensorFlow, PyTorch, and Cursor, NLP, and LLM benchmarking.
  • Experience using AI development tools to create test plans, develop test cases, and automate test cases.
  • Experience with firmware, BMC/OpenBMC, network protocols, enterprise storage devices, PCIe buses and devices, I/O sub-devices, CPU and memory, ACPI, UEFI specifications, and Redfish is a strong advantage.
  • Experience with GitHub, GitLab, Gerrit, PXE, SLURM, Kubernetes, and Docker is a strong advantage.

Preferred Qualifications

  • Experience with AI-related tools, LLMs, and NLP.
  • Experience working with NVIDIA GPU hardware.
  • Understanding of Linux virtualization, including KVM and Docker orchestrated with Kubernetes.
  • Background in parallel programming, ideally CUDA or OpenCL.

Compensation and Benefits

  • Base salary for Level 3: USD 140,000–224,250 per year.
  • Base salary for Level 4: USD 168,000–270,250 per year.
  • Eligibility for equity and benefits.
  • Applications will be accepted at least until August 23, 2026.
  • NVIDIA is an equal opportunity employer committed to an inclusive work environment.

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