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Senior SoC Methodology Architect, VLSI Physical Design

NVIDIA
Posted onFeb 23, 2026
LocationSanta Clara, California, United States (Hybrid)
Employment typeFull-time
Salary$136k – $218.5k Yearly

NVIDIA powers the world's most advanced AI systems, autonomous vehicles, and data centers with industry-leading GPUs and accelerators. Delivering these breakthrough chips requires world-class physical design execution and deep expertise in EDA tool application. Our Physical Design Applications team partners directly with design teams to enable successful tape-outs through expert floorplan development, tool optimization, and hands-on technical support.

We are looking for a Senior SoC Methodology Architect with expertise in floorplanning, early feasibility analysis, placement, routing, and methodology development. You will work closely with chip architects, EDA tool developers, and design leads to create and enhance floorplans in the early stages of chip development. This role requires creativity and the ability to work independently. It offers exceptional intellectual freedom and the chance to explore various responsibilities. If you enjoy working in multiple technical areas and want to see your contributions, come to life in top-tier AI hardware, this opportunity is perfect for you!

What you’ll be doing:

  • Define and optimize top-level floorplan, including die size estimation, route planning and hierarchy definition and efficient partitioning

  • Drive internal tools and top-level floorplan methodologies for chip automation

  • Facilitate rapid analysis, and ensure the efficient execution of new chips on advanced process technologies.

  • Collaborate with tool developers, architects, designers, and the top-level integration team to proactively identify and resolve issues.

  • Examine and evaluate floorplans to detect potential issues and explore automated solutions.

  • Support multi-functional development, integration, providing guidance and technical support to internal partners.

What we need to see:

  • BS, MS, in Electrical Engineering, Computer engineering, Computer Science or equivalent experience

  • A deep hardware engineering background with a concentration in chip floorplan, placement, routing and design analysis

  • Experience with EDA tools, floorplanning and physical design methodologies (flow and tool development)

  • 4+ years of relevant work experience

  • Strong problem solving and analysis skills

  • Understanding of Verilog and synthesis

  • Python, Perl and C/C++ programming language experience

  • Strong communication and interpersonal skills

Ways to stand out from the crowd:

  • Experience in chip-level floor planning and physical design

  • Familiarity in Python scripting and development

  • Experience in collaborating across multiple teams

  • A tenacity for solving complex challenges

NVIDIA is widely considered to be one of the technology world’s most desirable employers. And due to outstanding growth, our teams are rapidly growing. If you are 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!

#LI-Hybrid

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.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until February 23, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA is the world leader in accelerated computing, pioneering the GPU and driving advances in AI, high-performance computing, gaming, autonomous vehicles, and robotics.

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