Senior Physical Design Engineer — AI-Driven Automation

Synopsys Inc; Hillsboro (OR); On-site; USD 140,000 - 190,000; Full time

Job summary

Synopsys Inc in Hillsboro, OR is seeking an experienced ASIC physical design engineer to drive tapeout-ready flows for advanced nodes. You will utilize Fusion Compiler, ICC2, and Cadence Innovus, while building TCL and Python automation that improves design quality and predictability.

You will collaborate with customers, R&D, and field teams to translate constraints into robust design solutions and participate in AI-driven optimization initiatives. Travel to customer sites is required as needed.

Qualifications

• 5+ years of hands-on ASIC physical design experience.
• Proficiency with TCL, Python, or Perl to build design flows.
• Experience with 7nm and below FinFET designs and multi-patterning.
• Familiarity with AI-driven optimization methodologies is a plus.
• Excellent communication and customer-facing skills.

Responsibilities

• Support customer engagements on advanced-node designs using Synopsys tools.
• Develop and enhance physical design methodologies and automation solutions.
• Debug placement, clock tree synthesis, routing, timing closure, and power issues.
• Deliver methodology recommendations tailored to customer constraints.
• Contribute to AI-driven optimization initiatives and product requirements.
• Travel to customer sites for onsite support and design reviews.

Skills

ASIC physical design

TCL scripting

Python scripting

Cadence/Synopsys tools

Automation flows

Education

Bachelor's degree in Electrical Engineering

Master's degree in Electrical Engineering

Tools

Synopsys ICC2

Fusion Compiler

Cadence Innovus

Job description

Synopsys Inc in Hillsboro, OR is seeking an experienced ASIC physical design engineer to drive tapeout-ready flows for advanced nodes. You will utilize Fusion Compiler, ICC2, and Cadence Innovus, while building TCL and Python automation that improves design quality and predictability.

You will collaborate with customers, R&D, and field teams to translate constraints into robust design solutions and participate in AI-driven optimization initiatives. Travel to customer sites is required as needed.