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Specialized ML+VLSI skillset reduces applicants despite metro location and mid-level experience.
Strong semiconductor EDA and ASIC domain knowledge makes skills less transferable across industries.
Explicit five-year requirement plus niche ML, EDA, and C++ expertise raises filtering rigor.
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Develop and prototype AI/ML driven automation solutions to improve efficiency and quality metrics (power, performance, area, verification) in SoC and IP design workflows.
Collaborate closely with cross-functional teams including architecture, IP design, SoC design, verification, and implementation to pilot AI/ML methodologies in production designs.
Engage with academic and industry AI/ML research communities to evaluate and integrate state-of-the-art AI/ML techniques like GenAI, Reinforcement Learning, Graph Neural Networks into VLSI CAD software tools.
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, or related fields with strong software development background.
Minimum 5 years of experience in developing complex software projects with hands-on programming skills in Python and C++.
Experience working in Unix/Linux environments with version control tools such as Git or BitBucket.
Strong analytical and problem-solving skills with understanding of software development and debug tools.
Experienced in VLSI CAD methodology or EDA tool development targeting design, verification, and implementation flows.
Familiar with semiconductor design constraints and flows including SDC, clocks, CDC, RDC, static timing analysis, power-aware methodologies like UPF.
Comfortable working in fast-paced, cross-functional, multi-site teams to integrate AI/ML innovations into advanced node SoC designs targeting Edge AI, automotive, and microcontroller products.