We are looking for a Senior QA Automation Engineer who is passionate about networking and eager to dive into hands-on testing. Our team ensures the quality of NVIDIA’s network solutions through feature analysis, manual, and Python-based automated testing. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re proactive, open to learning new things, and ready to grow, we want you on our team!
What you'll be doing:
Simulate and test full-scale network architectures using multiple network operating systems via WebUI, back-end, CLI, and shell.
Validate that simulation configurations and features align with real-world physical setups.
Review architectural designs and requirements for new product features.
Design and implement end-to-end tests for new features, including SW GA and maintenance releases.
Report and document bugs, assist in reproducing and debugging issues, verify R&D bug fixes, and raise unresolved issues.
Perform various system tests (regression, performance, functional, security, etc.).
Design, implement, and maintain automated tests and framework APIs in Python.
What we need to see:
Practical / BA or equivalent experience in Computer Science, Computer Engineering, or Electrical Engineering.
5+ years of hands-on experience in QA and/or Networking.
Solid networking knowledge and hands-on experience with switching and routing.
Strong automation/scripting skills in Python and Linux Bash.
Proficiency in Python OOP and experience writing automation for WebUI, SDK, and API using pytest and Playwright .
Ability to handle multiple tasks, prioritize effectively, and execute responsibilities independently.
Dedicated, able to work independently, and take ownership of tasks.
Confident and effective verbal and written communication skills in English.
Ways to stand out from the crowd:
Strong CCNA and/or ISTQB, or similar certifications.
Sophisticated experience with Python automation and source control tools (Git/SVN).
In-depth Linux and Linux kernel knowledge (LPIC-2 level).
Experience with virtualization environments (Linux KVM, VMware, ESXi).
NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Skills Required
- 5+ years of hands-on experience in QA and/or Networking
- Practical / BA or equivalent experience in Computer Science, Computer Engineering, or Electrical Engineering
- Solid networking knowledge and hands-on experience with switching and routing
- Strong automation/scripting skills in Python and Linux Bash
- Proficiency in Python OOP and experience writing automation for WebUI, SDK, and API
- Confident and effective verbal and written communication skills in English
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
