Senior VLSI Library Methodology Engineer
NVIDIAJob Title
Senior VLSI Library Methodology Engineer
Role Summary
Design and build scalable automation and verification infrastructure for library analysis, quality validation, documentation, and deployment in NVIDIA's physical design flows. Collaborate with methodology, library, design, and build teams to improve quality, efficiency, and scalability on advanced process nodes.
Experience Level
Senior — typically 4+ years of relevant experience in library methodology, physical design, CAD, design automation, or VLSI infrastructure development.
Responsibilities
Primary responsibilities include:
- Architect, specify, and implement scalable automation systems for verification, issue checking, reporting, and release readiness across GPU and SoC flows.
- Build and enhance end-to-end infrastructure: analysis pipelines, regression frameworks, dashboards, and reporting systems with focus on maintainability and scale.
- Develop automated library analysis, validation, and quality-control flows; optimize runtime, capacity, and resource usage for large-scale analysis.
- Integrate quality systems with design, CAD, and library teams and improve cell design methodologies.
- Define and implement methodologies for issue triage, data integrity, quality metrics, and release criteria to improve visibility and decision-making.
Requirements
Must-have:
- 4+ years experience in library methodology, physical design, CAD, design automation, or related VLSI infrastructure development.
- Strong software development skills in Python, C++, or Perl; experience building workflow automation, data pipelines, validation frameworks, and dashboards.
- Experience designing and delivering production-quality technical systems with attention to specification, scalability, and operational robustness.
- Hands-on experience with industry-standard EDA tools (for example Innovus, Fusion Compiler, Crosscheck, Virtuoso) including scripting, customization, or tool integration.
Preferred / Nice-to-have:
- Understanding of how library models are consumed in synthesis, place-and-route, timing closure, and power analysis.
- Experience building quality systems for library modeling and validation, including contextual model calibration.
- Experience tracking metrics such as validation pass rates, regression health, issue trends, release readiness, and resource utilization.
- Applied AI/ML/LLM experience to improve EDA workflows or automation systems.
Education Requirements
M.S. in Electrical Engineering, Computer Engineering, Computer Science, or a related field preferred; equivalent practical experience is accepted.
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.
