Join our GPU Software Quality Assurance team as a Tools Development Engineer and leverage your expertise in AI technologies to revolutionize test automation. This role requires a deep understanding of Windows operating systems and extensive knowledge of GPU, CPU, and SoC architectures, including familiarity with PC I/O and common bus interfaces like PCIe, USB, and SATA.

We are looking for an individual proficient in applying AI to automate tests and optimize workflows. You will design and implement advanced testing solutions for NVIDIA's device driver software and SDKs, contributing to the continuous improvement of deliverable quality.

Design and implement automated tests using AI technologies for NVIDIA's device driver software and SDKs on Windows platforms. Develop tools and frameworks in Python or C# to automate and optimize GPU testing workflows. Build innovative solutions to expand software testing capabilities and drive test automation initiatives. Identify, isolate, and debug defects, contributing to root cause analysis and solutions. Measure and improve code coverage, accelerate development and test workflows with custom applications, and ensure compatibility across various products.

Provide peer code reviews, analyze test coverage reports, and escalate critical issues. Participate in root cause analysis for continuous process improvement. Effectively estimate and prioritize tasks for realistic delivery schedules. Collaborate closely with leadership to report progress and generate actionable insights.

A Bachelor's or Master's degree in Computer Science, Electronics & Telecommunication, or an equivalent field, coupled with strong academic records or relevant experience. A minimum of 3 years of programming experience in Python, C#, or a similar language, with a solid grasp of Object-Oriented Programming concepts. Proven experience developing Python scripts using application development concepts, including dictionaries, tuples, and RegEx. Working knowledge of databases and storage technologies such as SQL, MongoDB, and Elasticsearch. Demonstrated experience working with Windows OS and a comprehensive understanding of GPU, CPU, and SoC architectures.

Experience utilizing AI tools for test case automation and end-to-end QA workflows is essential. Strong communication and interpersonal skills are required for effective cross-team collaboration. Excellent analytical and problem-solving abilities, coupled with a highly organized, proactive, and quick-learning mindset, are crucial for success in this fast-paced engineering environment.