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.
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.
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.
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.
Skills Required
- BS or higher in Computer Science, Electronics, or related discipline, or equivalent experience plus 5+ years QA experience
- Proficient in validating web-based UIs and RESTful APIs via code
- Unix/Linux and shell programming skills
- Working command of Python programming language
- Familiarity with networking protocols
- Experience developing test cases and performing failure root cause analysis
- Experience automating manual tests and building/implementing test frameworks
- Experience integrating automation testing into CI/CD and discovery pipelines
- Good command of cloud management systems, Kubernetes, and supporting cloud infrastructure (e.g., Grafana)
- Hands-on experience with LLMs, including prompt engineering, fine-tuning, or integration into QA workflows
- Experience fine-tuning or training models for QA-specific tasks
- Strong QA skills: attention to detail, problem-solving, data analysis, quality standards, and time management
- Excellent written and verbal English communication
- Track record identifying areas for process improvement
- Experience with scalability or performance testing
- Experience building AI systems (RAG, MRC, AI agents) or AI-powered test generation tools
- Experience with NVIDIA GPU hardware
- Experience with data analysis and system monitoring across distributed systems
- Experience with Golang
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
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.”
.png){kind=logo}
