AI Yield Analytics Engineer

Project

Work done for a product or program.

• Build models that link inline metrology and defect data to final test yield.
• Create wafer map pattern recognition to detect systematic signatures.
• Design anomaly detection for process equipment and parametric data.
• Deploy models into fab and test data platforms with monitoring.
• Translate model findings into actionable recommendations for process teams.
• Maintain data quality rules across MES, metrology and ATE sources.

Function

Work that keeps the discipline running: methods, tools, suppliers and people.

• Develop automated defect classification from wafer inspection images.

Project

1. Produce and hand over the role's key deliverables
   • Yield prediction models
   • Defect classification pipelines
   • Excursion alert systems
   • Root-cause analysis reports
2. Support programsGeneral
   • Agree what each program needs
   • Deliver in time for milestones
3. Manage issuesGeneral
   • Track requests to closure
   • Escalate risks

Function

1. Run the functionGeneral
   • Maintain policies and processes
   • Keep records and controls
2. ImproveGeneral
   • Report performance
   • Lead improvement work