Job Description
NVIDIA is well positioned as the ‘AI Computing Company’, our GPUs being the brains that power modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We are looking for a Senior Software QA Test Development Engineer to join in the mission of crafting a distributed technology for all NVIDIA teams that remotely manage 10s of 1000s of resources in a simple and controlled fashion, allowing engineers to focus on engineering and automation, rather than being burdened by manual operational tasks.
SWQA test developer engineers at NVIDIA are responsible for creating test plans, execution, and reporting, as well as developing scripts for test automation, designing and developing tools for the QA team, and developing integration tests for validation. As a test developer, you must identify weak spots and constantly design better and more creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA’s products. The ideal candidate must have strong programming skills and hands-on experience using AI development tools to improve quality and productivity across the end-to-end QA workflow. This includes leveraging AI assistants for test automation, code generation, debugging, and enhancing testing efficiency. During the interview process, we will assess your ability to effectively use AI development tools and evaluate your programming capabilities to ensure you can deliver high-quality solutions.
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Responsibilities
Review product requirements and develop test matrix.
Build testing-related documentation, including test plans, test approach, test cases and bug reports assessing quality and associated risks.
Manage bug lifecycle and co-work with inter-groups to work towards solutions.
Automate manual tests and assist in the architecture, building and implementing test frameworks.
Enhance the existing testing frameworks used in the organization by our engineers, including yourself, for areas such as UIs, REST APIs, process automation and performance validation.
Support a reliable fast feedback loop by integrating automation testing in CI and discovery pipelines.
Proficient with web based UI and RESTful APIs validation via code as well as Unix/Linux and shell/python programming skills.
Familiarity with networking protocols as well as working command of the Python programming language.
Rich experience in test cases development and failure root cause analysis.
Track record in identifying areas of process improvement
Good command of Cloud management systems and Kubernetes and supporting cloud infrastructure (Grafana etc)
Experience with building and handling CI/CD pipelines.
Hands-on experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, or integration into QA workflows
Fine-tuning or training models for QA-specific tasks - adapting LLMs or other models specifically for testing, documentation analysis, or requirement validation
Good QA sense including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc.
Excellent communicator, fluent written and verbal English.


