Senior DGX Cloud Test Development Engineer, SDET

Overview

• 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-scale failure testing, using tools such as KWOK, Chaos Monkey, or similar frameworks.
• Strong communication, problem-solving skills, and curiosity for complex technology Ways to stand out from the crowd: 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.
• We provide reasonable accommodations for qualified individuals throughout the application and hiring process.