Senior VLSI Library Methodology Engineer

Job Title

Senior VLSI Library Methodology Engineer

Role Summary

Design and implement scalable automation and verification infrastructure for library analysis, validation, and release readiness across GPU and SoC physical design flows. Work with methodology, library, CAD, and design teams to improve library quality, efficiency, and scalability for advanced process nodes.

Experience Level

Senior. The posting specifies experience in the field; candidates typically have 4+ years in library methodology, physical design, CAD, design automation, or VLSI infrastructure development.

Responsibilities

The core responsibilities focus on architecture, implementation, and integration of large-scale automation and quality systems for library and physical design flows.

• Architect, specify, and implement scalable automation systems for library examination, verification, issue checking, reporting, and release readiness across GPU and SoC flows.
• Build and maintain end-to-end infrastructure: analysis pipelines, regression frameworks, dashboards, and reporting systems with emphasis on usability and maintainability.
• Develop automated library analysis, validation, and quality-control flows using modern scripting and EDA tools; optimize for runtime and resource efficiency at scale.
• Collaborate with design, CAD, and library teams to integrate quality systems, improve cell design methodologies, and apply adaptive threshold partitioning.
• Define and implement issue triage, data integrity checks, quality metrics, and release criteria to improve visibility and decision-making.

Requirements

Must-have technical skills and experience to perform the role.

• 4+ years of relevant experience in library methodology, physical design, CAD, design automation, or VLSI infrastructure development.
• Strong software development skills in Python, C++, or Perl; proven experience building workflow automation, data pipelines, validation frameworks, and dashboards.
• Experience designing and implementing production-quality systems with attention to 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.
• Ability to balance analysis quality with runtime, compute capacity, and infrastructure efficiency in large-scale environments.

Education Requirements

M.S. in Electrical Engineering, Computer Engineering, Computer Science, or a related field — or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.