EDA Methodology Architect

Details

NVIDIA's success builds on a foundation of industry-leading hardware. The team develops internal EDA tools by combining advances in parallel computing, machine learning, and specialized algorithms for VLSI design. This role defines and owns the next-generation RTL2GDS flow for advanced nodes (3nm and below) and high-performance GPU, CPU and SoC designs.

Responsibilities

• Work directly with core P&R engine developers to define real-world optimization problems, shape requirements and roadmaps, and provide detailed feedback on engine behavior, QoR, and scalability.
• Define and roll out next-gen flows, including refactoring legacy flows and consolidating ad-hoc solutions into scalable, maintainable frameworks used across multiple design teams.
• Design and run rigorous A/B and multi-variant experiments to compare flows, engines, and tool settings.
• Develop Python-based analytics and ML/GenAI techniques to mine large QoR datasets, recommend flow settings, and automate analysis.
• Perform deep root-cause analysis on QoR issues across engines, tools, and flows, and drive methodologies to resolve timing closure and performance limiters.
• Partner with architecture, RTL, DFT, synthesis, physical design, power, signoff, and CAD/methodology teams as a technical leader and bridge.
• Drive aggressive PPA and schedule targets and the adoption of new tools and flows across the company.

Requirements

• BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
• 8+ years of physical design experience, with deep expertise in industry-standard tools such as ICC2/Innovus and PrimeTime/Tempus.
• Extensive hands-on P&R experience taking complex blocks or chips to tape-out with aggressive PPA targets.
• Proven skills in Python, Perl, and TCL flow development.
• Experience across RTL2GDS flow stages: RTL, DFT, synthesis, placement, optimization, CTS, routing, and signoff.
• Strong problem-solving skills and self-motivation, demonstrated by simplifying complex environments and modernizing legacy tools and processes.
• Excellent communication and collaboration skills, with a track record of driving consensus across distributed design, CAD, and R&D teams.

Ways to Stand Out

• Experience collaborating with EDA or internal R&D teams on core engine development, co-defining features, developing benchmarks, and leading validation and deployment.
• Expertise in designing and automating A/B tests and large-scale regressions, and analyzing large QoR datasets to understand trends and drive root-cause analysis.
• Background in advanced-node and large-scale designs with exposure to advanced-node challenges (DFM, variability, EM/IR, power integrity).
• Hands-on experience applying AI/ML or GenAI to physical design, QoR analysis, or flow development.

Compensation & Additional Information

• Base salary range: 168,000 USD - 264,500 USD (determined based on location, experience, and pay of employees in similar positions).
• Eligible for equity and benefits.
• Applications accepted at least until January 13, 2026.
• NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.