Yield Engineer - Process Integration Job Sugar Land area,Texas USA,Engineering

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

This position will analyze wafer fabrication, equipment, metrology, device-test, and reliability data to identify yield trends, process variation, and improvement opportunities. The Yield Engineer will work closely with Fab Process Engineering, R&D, Equipment Engineering, Quality, Test, and Reliability teams to improve process stability, process capability, product yield, and reliability.

The successful candidate will combine semiconductor process knowledge with strong statistical analysis and structured problem-solving skills. The engineer will plan and analyze designed experiments, monitor critical process indicators, investigate yield excursions, and translate analytical findings into process-improvement actions.

Responsibilities

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.

Qualifications

Required

Bachelor’s degree in electrical engineering, Materials Science, Chemical Engineering, Physics, Statistics, or a related technical field.
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.
Ability to work effectively with Fab, R&D, Equipment Engineering, Quality, Test, and Reliability teams.
Strong technical communication and structured problem-solving skills.

Preferred

Master’s degree or above in Engineering, Materials Science, Physics, Statistics, or a related field.
Experience in optoelectronics, photonics, compound semiconductor, or IC manufacturing.
Experience with InP, GaAs, silicon, or related semiconductor technologies.
Experience analyzing wafer maps, defect inspection, equipment history, inline metrology, electrical test, optical test, burn-in, or reliability data.
Experience improving process capability, Cp, Cpk, yield, scrap, or rework through statistically designed…