Staff GenAI Engineer - Early PDN Modeling
Core
Embed AI and automation into Power Delivery Network (PDN) analysis, power integrity validation, and optimization workflows to accelerate memory design and reduce manual effort.
Role type
Staff GenAI Engineer (Early PDN Modeling)
Builds
AI-enabled power integrity validation tools, predictive models for IR drop/voltage droop, and automated design-space exploration for memory products.
Domain
Semiconductor / Memory Design / Power Integrity / EDA
Deliverable
production ML models
Required skills
Python, Machine Learning, Generative AI, Power Delivery Networks (PDN), IR drop analysis, Voltage integrity, EDA workflows, Data analysis, Automation, Circuit design, Physical design, Package design
Preferred skills
Graph Neural Networks, Surrogate modeling, Large Language Models, Agentic AI systems, Memory subsystem power delivery, Package-PDN interactions, Full-chip power integrity methodologies, EDA tools for power integrity
Technologies
Python, Graph Neural Networks, Large Language Models, Agentic AI systems
Responsibilities
Embed AI into PDN analysis and power integrity validation workflows; Apply data-driven methods to predict IR drop, voltage droop, and electromigration risk; Enable AI-assisted optimization of power grid architectures and bump planning; Leverage historical design and silicon data for predictive insights; Develop ML solutions to automate root-cause analysis and design-space exploration; Collaborate across design, CAD, package, and product engineering teams to scale AI methodologies.
Seniority
Staff, hands-on IC with strategic impact