Automation and Tools Engineer

As a Software Automation & Tools Development Engineer at NVIDIA, you will play a crucial role in designing and implementing tests for NVIDIA software products to detect defects early in the software development lifecycle. Your responsibilities will include creating automated tests for NVIDIA's device driver software on Windows, executing these tests, identifying defects, and reporting them. Additionally, you will be tasked with measuring code coverage, analyzing and enhancing code coverage, and developing applications and tools that provide data-driven insights for development and test workflows. In this position, you will be expected to write maintainable, reliable, and well-detailed code, conduct peer code reviews, debug issues to determine root causes, and participate in post-mortem analyses with team members. You will be instrumental in automating and expanding software testing, estimating and prioritizing tasks for a realistic delivery schedule, and collaborating closely with leadership to provide progress updates through effective reports. Your role will involve addressing challenging technical and process issues to enhance workflows and ensure reliability. To be successful in this role, you should possess a degree in Computer Science, IT, or Electronics engineering, along with 8-10+ years of programming experience in C#, .Net, and Python, applying Object-Oriented Programming concepts. You should have proficiency in working with databases and storage technologies like SQL and Elasticsearch, as well as familiarity with version control tools such as Git and Perforce, and code review tools. Your ability to debug issues using tools like WinDBG or gdb is essential, along with your aptitude for collaborating with multiple development teams to enhance test code coverage. Strong written and verbal communication skills, along with the capability to work effectively in a fast-paced environment with a team of engineers, are key requirements for this role. For those looking to distinguish themselves, a background in projects involving Machine Learning or Deep Learning, as well as experience with cloud services and virtualization, will set you apart from the crowd.,