You’ll focus on improving PCB material modeling quality and simulation-to-measurement correlation to inform design decisions for new technologies and designs. You thrive on bridging the gap between modeled and measured results, enjoy cross-functional collaboration with hardware engineering teams, and are motivated to drive adoption of proven methodologies across a diverse set of products.

Minimum Qualifications
Master’s degree in Electrical Engineering or a relevant field of study.
3+ years of related work and relevant academic experience.
Hands-on experience with EM simulation vendor tools — such as HFSS or similar
Expertise in AI/ML methodologies — such as DNN, PINN, or gradient boosting
Good understanding of Electromagnetics.
Experience with scripting languages.

Preferred Qualifications
PhD in Electrical Engineering or a relevant field.
A deep understanding of PCB material characterization methods and material property modeling across environmental conditions is part of your expertise.
Experience with VNA-based S-parameter measurement, TRL/TDR calibration, and de-embedding workflows.
Strong understanding of simulation-to-measurement correlation workflows, including de-embedding techniques.
Excellent communication, presentation, and organizational skills to collaborate effectively across teams.