We are looking for a Software Verification & Infrastructure Engineer to design and expand the verification infrastructure of NVIDIA’s hardware simulation platform. The role combines strong software development skills with a verification mindset - building tools, automation, and frameworks that ensure accuracy, performance, and scalability of large-scale simulations. This simulation platform enables NVIDIA engineers across firmware, SDK, and OS domains to develop and test their code without relying on physical hardware.
What you'll be doing:
Develop and maintain the simulation’s verification system and supporting infrastructure - design frameworks and tools that enable efficient test creation, execution, and analysis for complex hardware simulations.
Implement and automate multi-node verification tests to validate system behavior, scalability, and performance across distributed environments.
Own CI/CD pipelines and testing automation ensuring reliability, repeatability, and fast iteration cycles for simulation releases.
Collaborate closely with design and DevOps teams to integrate new hardware models, test scenarios, and infrastructure improvements.
Drive innovation in simulation verification - continuously improve coverage, debug efficiency, and system authenticity.
B.Sc. or equivalent in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related field.
4+ years of hands-on experience in Python and C/C++, with strong debugging and object-oriented design skills.
Experience in verification infrastructure or test automation frameworks (e.g., Pytest, custom frameworks).
Solid understanding of Linux systems - including scripting, debugging (gdb), and containerized environments (e.g., Docker).
Familiarity with CI/CD pipelines and DevOps workflows (Jenkins, Git, Gerrit).
Knowledge of Inter-Process Communication (IPC) mechanisms (sockets, message queues, shared memory).
Creative, proactive, and detail-oriented team player with a passion for reliable systems.
Ways to Stand Out from the Crowd
Experience in simulation or emulation systems, especially those modeling hardware or distributed environments.
Familiarity with networking or GPU architectures, or other hardware/software co-simulation domains.
Proven experience developing multi-node or multi-platform verification environments.
Strong background in automation, CI integration, and test scalability.
Excellent communication skills and ability to collaborate across design, firmware, and infrastructure teams.
NVIDIA is committed to fostering a diverse work environment and is proud to be an equal-opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, disability status or any other characteristic protected by law.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
