Yield Engineer, Process Integration - Data-Driven, On-Site

Applied Optoelectronics, Inc.; Sugar Land (TX); Sur place; USD 85 000 - 135 000; Plein temps

Avantages offerts par ce poste

Relocation package available within US

Immigration sponsorships (Must be US-)

Résumé du poste

Applied Optoelectronics, Inc. (AOI) seeks a Yield Engineer to join the Process Integration group at its Sugar Land facility.

You will analyze wafer fabrication, equipment, metrology, device-test, and reliability data to identify yield trends and opportunities for improvement, partnering with Fab, R&D, Quality, and Reliability teams. The role combines semiconductor process knowledge with strong statistical analysis to plan designed experiments, monitor critical indicators, and translate findings

Qualifications

• Three or more years of experience in semiconductor manufacturing, process engineering, yield engineering, process integration, product engineering, or reliability engineering.
• Strong knowledge of statistical data analysis, including SPC, control charts, process capability, hypothesis testing, regression, ANOVA, and DOE.
• Strong working knowledge of JMP or similar statistical-analysis software for manufacturing-data analysis.
• Ability to analyze large datasets and translate statistical results into practical process actions.
• Good understanding of semiconductor fabrication processes, equipment, metrology, and manufacturing controls.
• Experience investigating process excursions, yield loss, process variation, or reliability failures.
• Demonstrated ability to connect semiconductor process variation with device performance, yield, or reliability results.

Responsabilités

• Analyze fab process, equipment, metrology, device-test, yield, and reliability data to identify trends, patterns, correlations, and sources of variation.
• Monitor yield by product, process step, tool, recipe, lot, wafer, and time period.
• Develop and maintain SPC charts for critical process parameters and product characteristics.
• Evaluate process performance using Cp, Cpk, and other statistical measures, and work with process owners to improve process capability.
• Plan, monitor, and analyze designed experiments to improve process performance, stability, yield, and reliability.
• Define yield metrics, analysis plans, data grouping, and comparison methods in collaboration with process owners and the Manufacturing Data Engineer.
• Establish appropriate process controls, monitoring methods, and reaction plans for critical process and product parameters.
• Identify abnormal process behavior and support the timely investigation of manufacturing excursions.
• Lead or support yield-loss investigations using wafer maps, defect data, equipment history, metrology results, device-test data, and reliability results.
• Work with Fab Process Engineering and Equipment Engineering to understand process- and tool-related variation.
• Collaborate with R&D to transfer new products and processes into manufacturing with appropriate controls and yield-monitoring plans.
• Partner with Quality and Reliability teams to connect fab process conditions with burn-in, reliability, and product-performance results.
• Prioritize yield-loss mechanisms based on technical impact, statistical evidence, and business importance.
• Recommend corrective actions and verify their effectiveness through follow-up experiments and production data.
• Prepare clear yield reports, trend charts, wafer maps, DOE summaries, and technical presentations for engineering and management.
• Document investigation results, process improvements, corrective actions, and lessons learned.

Connaissances

Statistical analysis

Structured problem solving

Data interpretation

Technical communication

Formation

Bachelor’s degree in electrical engineering/Materials Science/Physics/Statistics or related field

Outils

JMP

Python

SQL

Description du poste

Applied Optoelectronics, Inc. (AOI) seeks a Yield Engineer to join the Process Integration group at its Sugar Land facility.

You will analyze wafer fabrication, equipment, metrology, device-test, and reliability data to identify yield trends and opportunities for improvement, partnering with Fab, R&D, Quality, and Reliability teams. The role combines semiconductor process knowledge with strong statistical analysis to plan designed experiments, monitor critical indicators, and translate findings