Software Quality Assurance Engineer - 2026 New College Grad

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Software Quality Assurance Engineer role focused on testing and validating NVIDIA's Workstation and Virtualization products. The role involves reproducing customer-reported issues, performing root cause analysis, and verifying fixes. A key aspect is building AI-driven tools to improve workflow efficiency and bug reproduction. Experience with virtualization platforms, scripting (Python, C#, C++), and debugging tools is required. Familiarity with Generative AI platforms and LLMs is a plus.

What you'd actually do

  1. Reproduce issues reported by OEMs, enterprise customers, and partners.
  2. Collaborate with software developers, program managers, and customers to determine root causes, and verify defect fixes.
  3. Validate NVIDIA products on customer-specific platforms and configurations to ensure compatibility and reliability.
  4. Build Python, C#, and C++-based scripts and diagnostic tools aimed at increasing bug reproduction and troubleshooting efficiency.
  5. Build AI-driven tools and technologies that improve workflow efficiency.

Skills

Required

  • Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Electronics, Software Engineering, or related fields.
  • Proficient in Windows, virtualization technologies (VMware ESXi, Citrix Hypervisor, Microsoft Hyper-V, KVM) and scripting/automation (Python, PowerShell, Bash).
  • Proven ability to troubleshoot and resolve complex hardware and software issues.
  • Solid knowledge of PC architecture, supercomputers, and computer clusters, including caches, buses, memory controllers, DMA, and related components.
  • Extensive experience building, configuring, and troubleshooting PCs and servers.
  • Hands-on experience with debugging tools, memory dump analysis, remote debugging and Windows performance tracing tools (e.g., ETW).
  • Knowledge of graphics technology such as DirectX (DX), OpenGL (OGL), Windows Display Driver Model (WDDM), CUDA, and OpenCL.

Nice to have

  • Expertise in planning, installing, and optimizing virtualization environments (VMware ESXi, Citrix Hypervisor, Microsoft Hyper-V, and KVM).
  • Strong working knowledge of Linux distributions (e.g., Red Hat, Ubuntu).
  • Experience using Generative AI platforms / LLMs such as Gemini, Claude, Copilot, etc. to develop tools powered by artificial intelligence.

What the JD emphasized

  • AI-driven tools
  • Generative AI platforms / LLMs