GPU Unit Verification Engineer

Posted 2 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka
Junior
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
The GPU Unit Verification Engineer will verify the design and implementation of next-generation GPUs, ensuring compliance with hardware functional safety standards. Responsibilities include ownership of verification processes, developing reusable models, working with various teams, and utilizing advanced verification tools and methodologies.
Summary Generated by Built In

NVIDIA is seeking an outstanding Verification Engineer to verify the design and implementation of the next generation of the world’s leading GPUs. This position offers the opportunity to have real impact in a multifaceted, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of outstanding people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. At NVIDIA, our employees are passionate about parallel and visual computing. We're united in our quest to transform the way graphics are used to solve some of the most complex problems in computer science.

The GPU started out as an engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. NVIDIA is increasingly known as “the AI computing company.”

What you’ll be doing:

  • As a key member of our ASIC Verification team, you will verify the design and implementation of the industry's leading GPUs.

  • Own verification of the ASIC design, architecture, golden models and micro-architecture of the GPUs using advanced verification tools and methodologies.

  • Be responsible for ensuring that the verification meets the hardware functional safety standards required by Automotive applications.

  • Build reusable bus functional models, traffic generators, monitors, checkers and scoreboards following coverage driven verification methodology.

  • You are expected to understand the design and implementation, define the verification scope, develop the verification infrastructure and verify the correctness of the design.

  • Work with architects, designers, and pre and post silicon verification teams to accomplish your tasks.

What we need to see:

  • B.Tech./ M.Tech. with 2+ years or equivalent experience.

  • Proficiency in Verilog and C++ and C.

  • Familiarity with OOPs concepts.

  • Hands-on experience in verification at Unit/Sub-system/SOC level.

  • Good understanding of computer architecture concepts.

  • Strong technical fundamentals with superior analytical skills and problem-solving skills.

  • Exposure to industry standard verification tools for simulation and debug.

Ways to stand out from the crowd:

  • Knowledge of Hardware functional safety protocols and processes.

  • Prior experience in 3D graphics processing or processor verification.

  • C/C++ programming language experience.

  • Experience in scripting and tool development using Perl and Python.

  • Excellent debugging skills.

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Top Skills

C
C++
Verilog
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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