GPU Verification Architect

This is an outstanding opportunity to join a world-class team and play a pivotal role in crafting the future of GPU technology. At NVIDIA, you will work with dedicated individuals in an inclusive and collaborative environment where your hardworking nature will drive flawless execution and ambitious projects. 

What you will be doing: 

• Define, build, and drive the verification test plan for specific GPU products to ensure outstanding performance. 

• Collaborate with multiple teams including Architecture, ASIC, DV, Emulation, and Infrastructure to achieve seamless integration and strictly adhere to project timelines. 

• Ensure reliable execution of the defined test plan, triage failures, and successfully implement fixes to drive bugs to closure. 

• Manage project timelines effectively, ensuring team alignment for smooth progression and flawless execution. 

• Monitor and anticipate resource requirements, determining needs throughout the verification process to compete effectively. 

• Continuously improve planning and process flow by defining and tracking important metrics. 

• Research and apply AI tools to streamline and optimize workflow, ensuring our processes remain brand new and innovative. 

• Guide the improvement of the simulation platform and expand other resources to support future GPU architectures. 

• Participate in hands-on programming to improve or develop tests, resolve bugs in models, and build scripts for regressions and report generation. 

What we need to see: 

• Bachelor’s degree (or equivalent experience) in Computer Science, Electrical Engineering, Computer Engineering, or a related field. 

• 8+ years of relevant work experience, or an MS with 5+ years of experience, or a PhD with 2+ years of experience. 

• Proven experience working in an architecture validation or full chip verification environment.

• Strong problem-solving and debugging skills, with a track record of driving issues to closure. 

• Proficient programming skills in C++, C, and scripting languages such as Python or Perl.  Go programming proficiency a plus. 

• Solid background in Computer Architecture with experience in modeling (System C & TLM preferred). 

• Good understanding of build systems (CMAKE, make), toolchains (GCC, MSVC), and libraries (STL, BOOST), as well as familiarity with CI systems (Docker, Jenkins). 

• Effective communication and interpersonal skills, with the ability to work successfully in a distributed team environment.