Senior GPU Validation Engineer

NVIDIA•Santa Clara, CA

1d•$140,000 - $270,250

About The Position

NVIDIA is seeking a creative, hands-on software engineer to improve software quality and customer experience for GeForce products. The role focuses on test-to-failure practices, applying AI technologies to automate test cases, and using an in-depth understanding of Windows and Linux operating systems. As a Software Development Engineer in Test, the successful candidate will contribute to the technical design and implementation of tests for NVIDIA software products, identify defects early in development, and build tools that accelerate execution workflows. The work covers NVIDIA device drivers and SDKs, GPU-domain testing, and data-driven improvements to development and test workflows. The role includes designing and implementing automated tests, developing end-to-end tests on Windows, executing manual and automated tests, measuring code coverage, debugging issues, and improving testing tools and frameworks. The engineer will collaborate with development teams and leadership, review peers’ code, estimate and prioritize work, and report progress. The position offers a base salary range of $140,000–$224,250 for Level 3 or $168,000–$270,250 for Level 4, plus equity and benefits.

Requirements

B.E./B.Tech degree in Computer Science, IT, or Electronics Engineering with strong academics, or equivalent experience.
At least 5 years of programming experience in Python, C, or C++, including applying object-oriented programming concepts.
Hands-on knowledge of developing Python scripts and application-development concepts such as dictionaries, tuples, regular expressions, and PIP.
Experience using AI development tools to create test plans, develop test cases, and automate test cases.
Experience testing RESTful APIs and conducting performance and load testing.
Experience working with databases and storage technologies such as SQL and Elasticsearch.
Good understanding of operating system fundamentals, PC hardware, and troubleshooting.
Debugging skills and experience with tools such as WinDBG or gdb.
Working knowledge of GPU devices and technologies such as DLSS, Frame Generation, Reflex, CUDA, and G-Sync.
Ability to collaborate with multiple development teams to gain knowledge and improve test code coverage.

Nice To Haves

Prior project experience building machine learning and deep learning applications.
Good understanding of testing fundamentals.
Strong problem-solving skills, including applying sound logic to isolate and regress issues.

Responsibilities

Design and implement automated tests using AI technologies for NVIDIA device driver software and SDKs across Windows and Linux operating systems.
Develop automated end-to-end tests for NVIDIA device drivers and SDKs on Windows.
Execute manual and automated tests, and identify and report defects.
Measure code coverage, analyze results, and drive coverage improvements.
Develop applications and tools that provide data-driven insights into development and testing workflows.
Build Python, C, or C++ tools, utilities, and frameworks to automate and optimize GPU-domain testing workflows.
Write maintainable, reliable, well-detailed code.
Debug issues and identify root causes.
Conduct peer code reviews, providing feedback on performance, scalability, and correctness.
Estimate and prioritize tasks to create realistic delivery schedules, and address challenging technical and process issues.
Generate and test compatibility across a range of products and interfaces.
Work with leadership to report progress through effective, impactful reports.
Collaborate with multiple development teams to gain knowledge and improve test code coverage.