Join our GPU SWQA team as a Tools Development Engineer, where you will play a crucial role in enhancing our testing capabilities.

This position requires significant expertise in AI for test automation and a deep understanding of Linux operating systems. A strong grasp of system architecture, PC I/O, and common bus interfaces like PCI-E, USB, and SATA is essential. Familiarity with general PC architecture components will be a valuable addition to your profile.

Design and build automated tests leveraging AI for NVIDIA's device driver software and SDKs across Linux platforms. Develop robust tools and frameworks in Python to streamline and optimize GPU testing workflows. Implement and execute both automated and manual tests, meticulously analyze results, and identify/report defects.

Drive test automation initiatives with innovative solutions. Expose defects, debug issues to their root cause, and contribute to their resolution. Measure and enhance code coverage for software under test. Develop applications and tools that accelerate development and testing cycles, writing clean, maintainable code. Validate compatibility across diverse products and interfaces, and perform comprehensive software application testing.

Provide peer code reviews focusing on performance, scalability, and correctness. Accurately estimate and prioritize tasks for efficient delivery schedules. Tackle challenging technical and process issues, collaborating closely with leadership to provide progress reports.

A Bachelor's or Master's degree in Computer Science or Electronics & Telecommunication, or equivalent practical experience, is required. You should have 3+ years of programming experience in Python, with a solid understanding of Object-Oriented Programming concepts.

Demonstrate hands-on experience developing Python scripts with application development principles (dictionaries, tuples, RegEx, PIP). Proficiency in working with databases and storage technologies such as SQL, MongoDB, and Elasticsearch is necessary. A strong understanding of OS fundamentals and PC hardware tuning, particularly in Linux, Unix, and Windows environments, is expected.

Experience utilizing AI tools for test case and end-to-end QA workflow automation is crucial. Excellent communication, analytical, and problem-solving skills are a must. The ideal candidate is organized, proactive, a quick learner, and thrives in a fast-paced team setting.