NVIDIA
Senior Software QA Test Development Engineer

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Senior Software QA Test Development Engineer
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.
What you’ll be doing:
- 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.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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What we need to see:
- BS or higher degree or equivalent experience in Computer Science, Electronics, or related discipline with 5+ years QA experience.
- 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.


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Ways to stand out from the crowd:
- Experience building AI systems such as RAG (Retrieval-Augmented Generation) pipelines, MRC (Machine Reading Comprehension) solutions, or AI agents.
- Building AI-powered test generation tools - using LLMs to automatically generate test cases, test code, edge cases, or synthetic test data.
- Experience working with NVIDIA GPU hardware is a strong plus.
- Scalability or performance testing knowledge is a plus.
- Experience with data analysis and system monitoring across distributed systems as well as experience with Golang.
NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all.
NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.
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