Network QA Engineer

Posted 2 Days Ago
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Yokneam
Junior
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The QA engineer will test and validate network products, automate tests, report bugs, and collaborate with various teams while ensuring quality standards.
Summary Generated by Built In

We are seeking an experienced QA engineer to join our SW/FW testing team. This position will be part of our growing team, which enables NVIDIA products to meet the industry-leading benchmarks of efficiency and quality. We develop a collaborative and inclusive work environment, where ideas are shared and innovation is encouraged. As a QA Engineer in this group, you will be immersed in the latest advancements and actively contribute to developing world-class products. Your efforts will directly impact the performance and quality of our offerings, ensuring they consistently meet industry-leading standards. We are looking for an ideal candidate with proven QA experience who will be actively involved in testing industry-leading features in the Networking sector, can acquire new feature knowledge, conduct both manual and automated tests, and contribute to the development of automation systems. The ideal candidate should bring a robust understanding for SW release cycle and the QA part in it.

What you'll be doing:

  • Review arch design and requirements documents for new features introduced in several domains like Infiniband and Ethernet Switches and NICs, Nvidia GPUs, NVLINK, Linkx and more.
  • Design, develop, and perform tests for the new features, as part of FW GA or update releases.
  • Automate newly added tests in the existing automation framework, and add new capabilities and features to the framework.
  • Report bugs found during execution, assist with reproduction and debugs to understand root cause, verify bug fixes provided by R&D team, and raise if not fixed.
  • Conduct tests in various areas, including regression, performance, functional, and security. Keep track of testing progress and generate summary reports of testing activities.
  • Fully collaborate with different external teams like : :product marketing, R&D, and verification.
  • Define and build setups topologies for appropriate product coverage.

What we need to see:

  • Practical / BSc in Computer Science or Electrical/Electronics Engineering
  • At least 2 years of proven experience in QA
  • Experience with QA methodologies, Test design, Bug prioritization, SW release workflows
  • Clear verbal and written communication, proficient in written and spoken English
  • Self-reliant individual, capable of planning and carrying out tasks within their assigned area
  • Personal: good interpersonal skills, quick learner, proactive, innovative, highly motivated, and committed

Ways to stand out from the crowd:

  • Experience with release management, V&V, E2E testing
  • Working in fast-paced environment with multiple parallel running activities
  • Knowledge/experience in Networking protocols
  • Scripting skills and proven experience in Python or other programming languages

At NVIDIA, we are dedicated to pushing technological boundaries and providing exceptional customer experiences. If you are ready to join a world-class team and contribute to the success of innovative products, we want to hear from you. Apply now and take the next step in your engineering career with NVIDIA.

NVIDIA is committed to fostering a diverse work environment and 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.

Top Skills

Networking Protocols
Python
Qa Methodologies
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The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

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.”

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