Your Job

• Implement DFT architectures including ATPG, MBIST, LBIST, scan insertion, and analog test features Execute all phases of physical design: synthesis, floorplanning, placement, clock tree synthesis, place-and-route, timing closure, power/noise analysis, and signoff verification.
• Implement design strategies to achieve performance, area, and power targets for customer-specific ICs under lead guidance.
• Apply re-use methodologies, leveraging standard IP blocks, libraries, and flows to accelerate project execution.
• Resolve timing, congestion, and power issues in high-speed, high-density designs using EDA tools and scripting.
• Collaborate with RTL design, verification, DFT, and package teams to integrate requirements and ensure design convergence.
• Perform physical verification (DRC, LVS) and support debug for clean tape-out deliverables.
• Automate flows with TCL, Python, or Perl scripts to improve productivity and repeatability.
• Analyze design metrics and contribute to process improvements through data-driven insights.

Other Responsibilities

• Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs.

Required Qualifications

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related field.
• 4+ years of hands-on physical design experience on SoCs, covering RTL-to-GDSII flows.
• Proficiency with EDA tools like Synopsys ICC2/Fusion Compiler, Cadence Innovus/Genus, or Mentor Calibre for synthesis, PNR, STA, and verification.
• Strong knowledge of STA (PrimeTime/Tempus), power analysis, and congestion mitigation techniques.
• Experience with scripting (TCL, Python, Perl) for flow automation and debugging.
• Familiarity with advanced nodes, multi-corner multi-mode (MCMM) analysis, and IP integration.
• Analytical mindset for tackling complex timing/power challenges and effective cross-team communication.

Preferred Qualifications

• Experience with custom silicon for automotive, high-performance computing, or AI applications.
• Proactive in adopting new tools, flows, and best practices for re-use and efficiency.
• Detail-oriented team player committed to quality and on-time delivery.