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As a QA Test Development Engineer at NVIDIA, you will have the opportunity to work with a team of dedicated professionals who are enthusiastic about advancing technology. You will play a crucial role in testing, test content development and validating our software releases, ensuring that our products meet exceptional quality standards. With our state-of-the-art infrastructure and advanced technologies, you will tackle stimulating and intricate challenges that directly impact the success of our products. Join us in revolutionizing the industry and shaping the future of computing.
What you'll be doing:
Develop detailed test plans and perform testing for Compute software releases on different platforms, such as Tesla GPUs, NVIDIA turnkey systems, and OEM systems.
Lead CUDA release efforts, gather automation requirements, and drive the development of automation tools and infrastructure.
Collaborate with the test development team to build and develop test content in C++.
Ensure the delivery of high-quality software by focusing on code coverage and maintaining automation tools and infrastructure.
Contribute to the automation of manual test cases and work closely with the automation infrastructure team.
Be responsible for testing cloud services, new GPU/system bring-up, and CUDA releases.
Enhance system performance and predictability through data analysis, while conducting release and regression tests for existing CUDA features.
Focus on enhancing the customer experience by improving the ease of use and optimizing performance.
What we need to see:
A Bachelor's degree in a related field (or equivalent experience), with a preference for candidates holding a Master's degree.
7+ years of experience in software QA and automation development.
Proven experience in leading projects and collaborating across functional teams.
Strong knowledge of parallel programming, ideally CUDA C/C++, and experience with scripting languages such as Python.
Development experience in a test support organization.
Solid understanding of QA methodologies and cluster management.
Proficiency in devising test strategies, crafting comprehensive test plans, and proficiently conducting tests.
Familiarity with embedded systems, Linux, Perl, Python, and bug logging.
Proficiency in building test setups and strong hardware and software triage skills.
Ways to stand out from the crowd:
Knowledge of testing and validating large-scale cloud infrastructure and/or distributed systems.
Familiarity with various cloud technologies such as Cloud Stack, Open Stack, Mesos, Hadoop, and Kafka, as well as containers like Docker.
Understanding of virtualization infrastructure software like HyperV and KVM.
Experience in machine learning, artificial intelligence, and computer vision would be a plus.
You will also be eligible for equity and .
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