EDA Methodology Architect

NVIDIA•Austin, CA

About The Position

NVIDIA's success builds on a foundation of industry leading hardware. We achieve distinction through extensive design optimization, including combining the best of external EDA with highly optimized, internal EDA tools. Our team develops these tools by fusing advances in parallel computing, machine learning, and specialized algorithms for VLSI design. We are seeking a Senior P&R Methodology Architect to define and own the next generation RTL2GDS flow for advanced nodes (3nm and below) and high performance GPU, CPU and SoC designs. You should have deep, hands‑on experience across the full RTL2GDS flow, with expertise in key stages such as RTL, DFT, synthesis, placement, optimization, CTS, routing, and signoff. Creativity and self‑drive to explore is required. Our engineers enjoy unusually high intellectual freedom and the ability to explore broad roles. If you like to work across many technical areas and see your successes directly realized in the world's best AI hardware, it does not get any better than this!

Requirements

BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
8+ years physical design experience, with deep expertise in industry standard tools like ICC2/Innovus, PrimeTime/Tempus, etc.
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.
Strong problem‑solving skills and self‑motivation, demonstrated by simplifying complex, cluttered environments and modernizing legacy tools and processes.
Excellent communication and collaboration skills, with a track record of driving consensus and solving complex issues across distributed design, CAD, and R&D teams.

Nice To Haves

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 will be a strong plus.
If working hands‑on from early architecture and RTL through silicon, and serving as the connector between core developers, methodology teams, and users, excites you, we want to hear from you.

Responsibilities

Working 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.
Defining and rolling out next‑gen flows, including refactoring legacy flows and consolidating ad‑hoc solutions into scalable, maintainable frameworks used across multiple design teams.
Designing and running rigorous A/B and multi‑variant experiments to compare flows, engines, and tool settings.
Developing Python‑based analytics and ML/GenAI techniques to mine large QoR datasets, recommend flow settings, and automate analysis.
Performing deep root‑cause analysis on QoR issues across engines, tools, and flows, and driving methodologies to resolve the ‘long tail’ of timing closure and performance limiters.
Partnering with architecture, RTL, DFT, synthesis, physical design, power, signoff, and CAD/methodology teams as a key technical leader and bridge.
Driving aggressive PPA and schedule targets and the adoption of new tools and flows across the company.