AI-Driven PDK Engineer for Next-Gen Semiconductors

Global Foundries; Town of Malta (NY); On-site; USD 69,000 - 120,000; Full time

Job summary

GlobalFoundries is seeking an AI-Enabled PDK Development Engineer to develop and support AI-guided physical-verification, extraction, and design documentation solutions. You will work with LVS, DRC, PEX, OPC, and Design Manual development teams to apply Python, ML, LLMs, and code-generation techniques in a rigorous, QA-driven environment.

The role emphasizes translating technology requirements into accurate, maintainable software, validating outputs, and contributing to model fidelity across

Qualifications

• Requires a degree in a relevant field (EE/CE/CS/Physics/Math).
• 2+ years AI/ML/software eng./data science experience preferred; 3-5+ for higher levels.
• Strong Python programming, maintainable code, testing, and version control.

Responsibilities

• Develop, test, and support PDK code and rule content for LVS/DRC/PEX/OPC.
• Apply AI-guided methods to generate, translate, review, debug, and regression-test rule decks.
• Build automated pipelines to convert process and design requirements into rules, tests, and docs.
• Create test layouts, golden references, coverage metrics, and regression suites.
• Analyze PEX/OPC outputs with silicon/process data to improve fidelity.

Skills

Python

AI/ML

Linux/Unix

English fluency

Other language (C/C++/Tcl/Perl/Java)

Education

Bachelor's or Master's in Electrical/Computer Engineering or related

Tools

Siemens Calibre

Synopsys IC Validator/StarRC

Cadence Pegasus/PVS/Quantus

Job description

GlobalFoundries is seeking an AI-Enabled PDK Development Engineer to develop and support AI-guided physical-verification, extraction, and design documentation solutions. You will work with LVS, DRC, PEX, OPC, and Design Manual development teams to apply Python, ML, LLMs, and code-generation techniques in a rigorous, QA-driven environment.

The role emphasizes translating technology requirements into accurate, maintainable software, validating outputs, and contributing to model fidelity across