GPU Verification Architect

Posted 4 Days Ago
Be an Early Applicant
Santa Clara, CA
Senior level
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
The GPU Verification Architect at NVIDIA will lead the development and execution of verification test plans for GPU products. The role involves collaboration with multiple teams to ensure project timelines are met, effective troubleshooting of failures, and programming for test development. Continuous improvement of processes and tools, including the application of AI, is also essential.
Summary Generated by Built In

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. 

The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and 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, veteran status, disability status or any other characteristic protected by law.

Top Skills

C
C++
Go
Perl
Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

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.”

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