NVIDIA
SeniorDGXCloudTestDevelopmentEngineer,SDET
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior DGX Cloud Test Development Engineer, SDET at NVIDIA. Skills: AI-powered tools for software testing, test case generation, defect detection, flaky test analysis, regression testing, test coverage optimization, cloud-native systems testing, test automation, scalable test frameworks. Use and develop AI-powered tools to make software testing smarter, faster, and more effective. Improve test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimizat”
What You'll Achieve.
make software testing smarter, faster, and more effective; reduce testing time; improve defect detection; increase test coverage; streamlined QA workflows; reduced manual effort
Industry & Context.
problem-solving
What They're Looking For.
Must Have
5+ years of QA, test automation, or software testing experience, Hands-on experience using AI tools to improve QA workflows, QA fundamentals, test strategy, test planning, and failure analysis skills, Proficiency with Unix/Linux and shell or Python programming, Experience with Kubernetes, containers, CI/CD pipelines, and cloud-native systems, Experience testing observability tools such as Prometheus, Grafana, ELK Stack, Datadog, or similar platforms, Experience with large-scale failure testing, using tools such as KWOK, Chaos Monkey, or similar frameworks
Nice to Have
Used AI to reduce testing time, improve defect detection, or increase test coverage, Built AI-driven solutions that streamlined QA workflows or reduced manual effort, Experience with SaaS or PaaS testing, Experience with NVIDIA GPU hardware or GPU-accelerated software
What You'll Do.
Use and develop AI-powered tools to make software testing smarter
Improve test case generation
and test coverage optimization
design and execute test cases
and report quality status
and regression testing for cloud-native systems
Automate test cases and contribute to scalable test frameworks
Manage the bug lifecycle
reproduce customer issues
How You'll Work.
Team & Collaboration
Work with product, engineering, and cross-functional teams to review requirements and define test strategies
Communication Scope
communication
Full Job Description
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. **What you’ll be doing:** * Use and develop AI-powered tools to make software testing smarter, faster, and more effective! * Improve test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimization. * Work with product, engineering, and cross-functional teams to review requirements and define test strategies. * Build test plans, design and execute test cases, and report quality status, risks, bugs, and results. * Perform functional, performance, fault-injection, reliability, and regression testing for cloud-native systems. * Automate test cases and contribute to scalable test frameworks. * Manage the bug lifecycle, reproduce customer issues, and verify fixes. **What we need to see:** * MS or PhD in Computer Science, Engineering, or a related field. * 5+ years of QA, test automation, or software testing experience. * Hands-on experience using AI tools to improve QA workflows. * Strong QA fundamentals, test strategy, test planning, and failure analysis skills. * Proficiency with Unix/Linux and shell or Python programming. * Experience with Kubernetes, containers, CI/CD pipelines, and cloud-native systems. * Experience testing observability tools such as Prometheus, Grafana, ELK Stack, Datadog, or similar platforms. * Experience with large-
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