Wafer Pattern QA Tech (12‑Hour Shift)

Texas Instruments; Lehi (UT); On-site; USD 60,000 - 90,000; Full time

Job summary

Texas Instruments seeks a detail-oriented PDE Product Test Technician for the LFAB team. You will inspect wafer maps to identify defect patterns and ensure only high-quality material proceeds to final testing and customer delivery.

This role emphasizes pattern recognition, troubleshooting, and automation; you will collaborate with engineers on process improvements and utilize AI-driven automation to streamline manufacturing workflows.

Qualifications

• High School diploma or GED required.
• Must be 18+ years old.
• 2 years semiconductor Technician experience OR 8 years non-semiconductor/military Technician experience.
• Willingness to work 12-hour compressed schedule with day/night shifts including weekends and holidays.
• Proficient in advanced Excel and data analysis.
• Experience with data visualization tools and SQL.

Responsibilities

• Perform high-level inspection of wafer maps to identify defect signatures.
• Apply Inking protocols to exclude suspect dies from the next manufacturing stage.
• Monitor SBL and CPO thresholds; escalate gaps to PDE Engineers.
• Act as liaison between PDE and Probe Sites; provide troubleshooting support.
• Maintain the Wafer Map Library and prepare technical documentation for Qualification Lots.
• Identify opportunities for automation and process improvements.

Skills

Advanced Excel

Analytical thinking

Data visualization

SQL

Python/Perl scripting

Linux basics

AI automation interest

Education

High School diploma or GED

Tools

Spotfire

Tableau

SQL

Python

Perl

Linux command line

Job description

Texas Instruments seeks a detail-oriented PDE Product Test Technician for the LFAB team. You will inspect wafer maps to identify defect patterns and ensure only high-quality material proceeds to final testing and customer delivery.

This role emphasizes pattern recognition, troubleshooting, and automation; you will collaborate with engineers on process improvements and utilize AI-driven automation to streamline manufacturing workflows.