Visual Inspection Shift Engineer: AI-Driven Yield

AOI

Sugar Land (TX)

On-site

USD 75,000 - 95,000

Full time

3 days ago
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Benefits offered by this job

Health plans
401(k) matching
PTO payout
Relocation package
Immigration sponsorships

Job summary

AOI in Sugar Land, Texas seeks a Shift Inspection Engineer to lead visual inspection of our laser wafer and chip production. You will drive improvements to defect detection, train production staff, monitor yield, and optimize inspection tools in a cleanroom environment.

The role requires a Bachelor’s degree in engineering or CS, experience with cameras/optics, and data analysis skills. You’ll work on-site with cross-functional teams and contribute to AI model retraining for better accuracy.

Qualifications

  • Bachelor's degree in engineering or computer science required.
  • Experience with cameras, optics, lighting for image capture and processing is preferred.
  • DOE and data analysis capability; troubleshooting skills desired.

Responsibilities

  • Learn and improve defect inspection system; implement improvements for overkill/escape defects.
  • Develop visual inspection recipes for new products.
  • Collect data from daily production to train AI models and reduce misdetection rate.
  • Review work orders rejected by QC; troubleshoot inspection issues.
  • Ensure uptime, cycle time and quality metrics with urgency on issue resolution.
  • Prepare weekly inspection yield reports and analyze trends.
  • Maintain hardware tool routines and qualify new tools.
  • Document process changes as SOPs.

Skills

Cameras & optics
DOE & data analysis
Troubleshooting

Education

Bachelor's degree in engineering or computer science

Tools

Microsoft Access
SQL

Job description

AOI in Sugar Land, Texas seeks a Shift Inspection Engineer to lead visual inspection of our laser wafer and chip production. You will drive improvements to defect detection, train production staff, monitor yield, and optimize inspection tools in a cleanroom environment.

The role requires a Bachelor’s degree in engineering or CS, experience with cameras/optics, and data analysis skills. You’ll work on-site with cross-functional teams and contribute to AI model retraining for better accuracy.

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