Bachelor’s degree in Electrical Engineering, Computer Science, or equivalent practical experience.
16 years of experience in Electronic Design Automation (EDA) tools and IP/chip design, physical design, including floorplanning, placement, routing, clock tree synthesis, and power optimization.
Experience working with EDA vendors and cross-functional teams to drive adoption of new methodologies and tools.
Experience in solving physical design issues with AI/ML algorithms and techniques.
Preferred qualifications:
Experience in developing AI/ML models for physical design optimization.
Experience with cloud-based Machine Learning (ML) frameworks and tools.
Experience in leading and mentoring technical teams.
Understanding of hardware acceleration platforms (e.g., GPUs, TPUs).
Understanding of physical design principles, EDA tools, scripting languages (e.g., Python, Perl, Tcl), and industry standard physical design flows.
Excellent problem-solving, investigative, communication, and teamwork skills.