NVIDIA has continuously reinvented itself over two decades. Our 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. Nvidia is a "learning machine" that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life's work to amplify human imagination and intelligence. Make the choice to join us today!

As a software engineer you will craft and implement APIs and services to support the execution of workflows to validate the design of NVIDIA's chips. The systems we develop will operate at a large scale, running millions of tests per day in a distributed cloud computing environment with thousands of heterogeneous servers to verify multiple designs in many configurations. You will continuously innovate and develop scalable, reliable, high-performance systems, and tools to enable the next generation of chips.

What you'll be doing:

Build microservices that are reliable, scalable, maintainable, and accessible to AI agents.
Improve current systems to enhance resource scheduling, optimize performance, increase reliability, and deliver higher throughput.
Develop streamlined, reliable interfaces optimized for usability and scalability across thousands of engineering users.
Join an agile and proactive software development team with very high production quality standards.
Participate in the full life-cycle of tool development, test, and deployment.
Partner with internal customers to analyze workflows and system environments, delivering solutions optimized for their specific requirements.
Play a key role in enhancing product quality and development efficiency of NVIDIA’s next-generation chips.

What we need to see:

Excellent software engineering skills, including applied knowledge of OOP, design patterns, distributed systems, multiprogramming, and microservices.
Skilled in Python and common service (FastAPI) and/or multiprogramming-related (asyncio) packages.
MS (preferred), BS, or equivalent experience in Computer Science/Engineering.
4+ years of experience.
Excellent planning, presentation, and general communication skills.
The flexibility and adaptability to work in an exciting environment with changing requirements.
Experience with distributed container orchestration systems like Kubernetes.

Ways to stand out from the crowd:

Experience developing and deploying automated distributed testing infrastructure.
Familiarity with EDA or related chip design and verification workflows.
A passion for improving the productivity and efficiency of other engineers.
Experience with noSQL database technologies like Redis and MongoDB.
Expertise in JavaScript, TypeScript, Perl, or C/C++.

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