Physical Design Staff Engineer

Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.

You have spent years in the trenches of physical design, where the difference between a chip that tapes out on schedule and one that doesn't often come down to a timing path you caught or a methodology decision you made six months earlier. You know that getting to signoff is not about running tools, it is about understanding what the data is telling you and building flows that make the next iteration faster and smarter.

You are the engineer who looks at a timing report and sees patterns, not just violations. When a clock tree is misbehaving or a design is bleeding power, you do not just fix the symptom, you trace it back to the root cause and build something that prevents it from happening again. Automation is not a buzzword to you, it is how you scale yourself across multiple projects without losing quality.

You have worked at advanced nodes where margins are thin and every decision counts. You know your way around ICC2 or Fusion Compiler well enough that you can tell when the tool is doing something unexpected, and you know how to script your way out of it. At Synopsys, you will work on real silicon with real constraints, and what you build will directly affect whether our customers can close their designs on time.

• Drive timing closure, signoff readiness, and PPA optimization for advanced-node customer designs, working across block, subsystem, and chip-level implementations
• Develop and enhance physical design methodologies and automation solutions using TCL, Python, Perl, or Pandas to improve design quality, predictability, and team efficiency
• Perform static timing analysis, clock-tree synthesis, and ECO implementation using tools like Prime Time, ICC2, Fusion Compiler, or Cadence Innovus
• Analyze design data and trends to identify bottlenecks, predict issues, and build flows that make the next tapeout smoother than the last
• Collaborate with cross-functional engineering teams including design, verification, and CAD to ensure successful silicon delivery
• Contribute to AI-assisted and machine learning-driven design optimization initiatives, applying data-driven approaches to solve complex implementation challenges
• Troubleshoot complex physical design problems that do not have obvious answers, and develop scalable technical solutions that work across multiple projects

• Your methodologies and automation will directly reduce design cycle time and improve first-pass silicon success for Synopsys customers building chips at 3nm, 2nm, and beyond
• The flows you build will be reused across multiple projects and teams, multiplying your impact across dozens of tapeouts
• Your timing closure expertise will help customers meet aggressive PPA targets that define whether their products succeed in the market
• The design data analysis and trend identification you perform will shape how future tools and methodologies are developed at Synopsys
• Your contributions to AI-driven design optimization will help define the next generation of physical implementation workflows
• The technical solutions you develop will become reference methodologies that other engineers learn from and build upon
• Your ability to troubleshoot complex corner cases will unblock critical customer programs and strengthen Synopsys relationships with leading semiconductor companies

• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, or a related technical field
• 5+ years of hands-on experience with ASIC physical design, implementation, and timing closure across block, subsystem, or chip-level designs
• Deep working knowledge of static timing analysis, clock-tree synthesis, signoff flows, and ECO methodologies
• Proficiency with industry-standard implementation tools such as Synopsys ICC2, Fusion Compiler, or Cadence Innovus
• Strong scripting and automation skills using TCL, Python, Perl, or similar languages to build flows and analyze data
• Experience with advanced-node semiconductor design at 7nm or below is a strong plus
• Exposure to machine learning, AI-assisted design optimization, or…