GPU Core Pipeline IP Verification Engineer

Posted 4 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
Hybrid
Junior
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Verify GPU ASIC IP and control subsystems at unit, subsystem, and SOC levels. Define verification scope, develop infrastructure, create golden models, validate RTL functionality and code coverage, and debug designs using simulation and verification tools. Collaborate with hardware architects and designers on implementation decisions. The role focuses on graphics and compute features for GPUs supporting consumer graphics, autonomous vehicles, and artificial intelligence applications.
Summary Generated by Built In

NVIDIA is seeking a highly enthusiastic and motivated Verification Engineer to verify the design and implementation of the next generation of control subsystems for the world’s leading GPUs. This position offers the opportunity to have real impact in a dynamic, 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 are 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 contribute to verifying graphics and compute features within an IP.

  • You will be responsible for IP-level verification of GPU ASICs, including the design, architecture, golden models, and micro-architecture, using advanced verification tools and methodologies.

  • You will work with the specifications and ensure functional and code coverage of all the RTL which you will verify.

  • 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 HW architects and designers to make the right implementation choices.

  • You will be working with architects, designers, and other members of your verification teams to accomplish your tasks.

What we need to see:

  • B.Tech./ M.Tech. with 1+ years of relevant experience

  • Familiarity with Verilog, C++ and OOPs concepts.

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

  • Background with design and verification tools (VCS or equivalent simulation tools, debug tools like Debussy, GDB).

  • Good understanding of computer architecture concepts.

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

  • Knowledge in SystemVerilog or similar HVL, experience in verification methodologies like UVM/VMM is highly desirable

  • Exposure to industry standard verification tools for simulation and debug

Ways to stand out from the crowd:

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

  • C/C++ programming language experience

  • Experience in scripting and tool development using Perl and Python

  • Excellent debugging skills

  • Good interpersonal & communication skills & dream to work as a great teammate

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.

#LI-Hybrid

Skills Required

  • B.Tech. or M.Tech. degree
  • At least 1 year of relevant experience
  • Familiarity with Verilog, C++, and object-oriented programming concepts
  • Hands-on verification experience at unit, subsystem, or SOC level
  • Experience with design and verification tools, including VCS or equivalent simulation tools
  • Experience with debug tools such as Debussy or GDB
  • Understanding of computer architecture concepts
  • Strong analytical and problem-solving skills
  • Knowledge of SystemVerilog or a similar hardware verification language
  • Experience with UVM or VMM verification methodologies
  • Experience in 3D graphics processing or processor verification
  • Experience with Perl and Python scripting and tool development
  • Excellent debugging skills
  • Strong interpersonal and communication skills

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
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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