NVIDIA Corporation

Senior VLSI Library Methodology Engineer

NVIDIA Corporation$136K — $264K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • M.S. in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
  • 4+ years in library methodology, physical design, CAD, or design automation.
  • Strong programming skills in Python, C++, or Perl for automation and data workflows.
  • Experience with production-quality system design, focusing on scalability and robustness.
  • Proficient with EDA tools such as Innovus, Fusion Compiler, or Virtuoso.

Responsibilities

  • Architect and implement scalable automation systems for verification and readiness across GPU and SoC flows.
  • Enhance infrastructure, focusing on usability and maintainability from analysis to reporting systems.
  • Develop automated library analysis and quality control flows tailored for large-scale analysis efficiency.
  • Collaborate with design and library teams to integrate and improve quality methodologies.
  • Define methodologies for data integrity and quality metrics, enhancing overall decision-making.

Benefits

  • Opportunity to work on cutting-edge AI and GPU technology.
  • Collaboration with a high-performing team of professionals.
  • Potential for career growth within a prominent tech company.
  • Engagement with advanced automation and verification systems.
  • Participation in a dynamic work environment promoting innovation.
Full Job Description
Are you excited to architect and build the automation infrastructure behind next-generation silicon design? We're seeking a Senior VLSI Automation Engineer to join our team and drive the development, specification, and implementation of scalable systems. These systems support library analysis, quality validation, documentation, and deployment for NVIDIA's Physical Design flows. In this role, you will help build robust, data-driven automation and verification infrastructure. You will collaborate with methodology, library, and build teams to improve quality, efficiency, and scalability on advanced nodes.

What you'll be doing:
  • Architect, specify, and implement scalable automation systems for examining, verifying, issue checking, reporting, and release readiness across GPU and SoC flows
  • Build and enhance end-to-end infrastructure, from analysis pipelines and regression frameworks to dashboards and reporting systems, with strong focus on usability, maintainability, and scale
  • Develop automated library analysis, validation, and quality control flows using modern scripting and EDA tools, including consideration of runtime, capacity, and resource efficiency for large-scale analysis
  • Collaborate with design, CAD, and library teams to integrate quality systems and improve cell design methodologies, applying adaptive threshold partitioning
  • Define and implement methodologies for issue triage, data integrity, quality metrics, and release criteria that improve visibility and decision-making across the flow


What we need to see:
  • M.S. in Electrical Engineering, Computer Engineering, Computer Science, or related field (or equivalent experience)
  • 4+ years of experience in library methodology, physical design, CAD, design automation, or related VLSI infrastructure development
  • Strong software development skills in Python, C++, or Perl, with hands-on experience building workflow automation, data pipelines, validation frameworks, and reporting/dashboard systems
  • Experience designing and implementing production-quality technical systems from an architectural and implementation point of view, including specification, scalability, and operational robustness
  • Hands-on experience with industry-standard EDA tools such as Innovus, Fusion Compiler, Crosscheck, Virtuoso, or similar, including scripting, customization, or tool integration


Ways to stand out from the crowd:
  • Understanding of how library models are consumed in chip design flows, including synthesis, place and route, timing closure, and power analysis
  • Experience building robust quality systems for library modeling, validation, or physical design automation, including exposure to contextual model calibration
  • Background in designing infrastructure that tracks critical metrics such as validation pass rates, regression health, issue trends, release readiness, and resource utilization
  • Experience balancing analysis quality with runtime, compute capacity, and infrastructure efficiency in large-scale automation environments
  • Applied AI/ML/LLM experience to improve EDA workflows, automation systems, or design methodologies


We welcome you join our team with some of the most hard-working people in the world working together to promote rapid growth. Are you passionate about becoming a part of a best-in-class team supporting the latest in GPU and AI technology? If so, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 31, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ

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