Inspection Shift Engineer (7am-7pm)

AOI; Sugar Land (TX); On-site; USD 75,000 - 95,000; Full time

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

Summary

We are looking for a Shift Inspection Engineer who will be in charge of our compound semiconductor Laser Wafer and Chip visual inspection to expand the capabilities of our semi-automated defect detection system in a cleanroom environment. Main tasks include visual inspection production line training for variety of product families, product inspection yield monitoring and improvement, inspection algorithm improvement, and regular inspection, maintenance, and optimization of tools/equipment.

Job Duties

• Learn current inspection system and implement improvement for defect inspection overkill and escape
• Development of visual inspection recipes for new products
• Perform sampling review of chip photos from daily production and continuously collect escaped and overkilled photos for AI model building and retraining to reduce misdetection rate
• Review work orders rejected by Outgoing Quality Control department
• Troubleshooting for work orders with inspection issues
• Ensure production line meet uptime, cycle time and quality metrics, have the sense of urgency on resolution of production issues
• Inspection yield report analysis on a weekly basis
• Current inspection of hardware tool routine maintenance and new tool qualification
• Document process changes/updates in format of Standard Operating Procedure
• Technical training for operators and technicians
• Regularly and effectively communicate status of activities/project updates with colleagues
• Overtime may be needed for production line needs

Qualifications

• Required: Bachelor's degree in engineering or computer science
• Software/ Hardware Knowledge:
  • Microsoft Access or SQL preferred
• Skills/ Abilities:
  • Knowledge of cameras, lenses, optics, lighting, and others for image capture and processing
  • DOE and data analysis capability
  • Trouble-shoot capability

Location

This position will be on-site based in Sugar Land, Texas.

WHY AOI?

• Flexible and competitive health (medical, dental, vision) plans offer the employee with the right options to meet individual needs
• Employer matching on 401(k) deferrals
• Unused PTO payout at end of the year
• Relocation package available within US
• Immigration sponsorships (Must be currently authorized to work in the US)

We do not accept unsolicited proposals from third-party recruiters or agencies. Contacting hiring managers directly may result in disqualification of submissions.