As a PPAC Optimization Engineer youll optimize the design and implementation methodology for cellular chips across multiple focus areas including area efficiency power optimization and design technology co-optimization. Your primary responsibilities will involve optimizing Power Performance Area and Cost efficiency metrics through various approaches:- Identify utilization bottlenecks in physical design and develop architectural design and implementation-level solutions to improve utilizations.- Develop and implement Vmin and power optimization methodologies- Perform design technology co-optimization analysis including optimal voltage point analysis for performance/power curves and identification of scaling trends and bottlenecks in new technology nodes- Collaborate closely with technology and IP teams to enhance efficiency through custom and semi-custom IP development- Conduct in-depth analysis of Frontend and Backend databases as well as post-silicon data to identify critical issues and improve PPA- Work closely with silicon technology front-end physical design CAD and other teams to develop innovative solutions and implement them on test chips
Minimum BS and 10 years of relevant industry experience.
VLSI background with hands-on experience in RTL to GDSII flows.
Prior experience in doing Power Performance Area and Cost optimizations for SoCs.
Experience with SoC power flows & Vmin optimization.
Experience with Design Technology Co-optimization identifying and solving scaling bottlenecks in new technology nodes.
Rapid prototyping and scripting of methodologies and test chip block implementation.
Solid understanding of Physical Design challenges proficiency with synthesis place and route tools and implementation exploration.
Experience with Metal stack optimizations.
Experience performing Early Tech node analysis to identify implementation bottlenecks.
Design Technology Co-optimization expertise.
Strong analytical skills and ability to identify and communicate high return on investment opportunities.
Ability to apply data science and ML analytics for Frontend and Backend databases as well as post-silicon data to identify trends & patterns and fine-tune implementation methodologies.
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