Lead Engineer, Automation and Application

Coherent • Sherman, TX

2d • Onsite

About The Position

Description Primary Duties & Responsibilities Lead the development, deployment, and production support of AI/ML-driven wafer-level and die-level image processing solutions for Automated Visual Inspection (AVI) tools used in front-end and back-end wafer fab operations. Design, implement, and sustain advanced vision and image processing pipelines, including Crack detection and advanced defect classification, Die-to-die and wafer-level image stitching, Optical inspection data analysis Develop, train, validate, and maintain machine learning models used in AI-powered optical inspection, ensuring robustness, accuracy, and scalability in high-volume manufacturing environments. Integrate AI/ML-based solutions with fab automation systems, leveraging in-situ equipment and process data to enable anomaly prediction and early detection for critical processes. Work hands-on in the fab environment with automation team members, operations, process engineering, and equipment engineering teams to deploy, debug, and sustain automation, inspection, and process control solutions. Ensure reliable data foundations for inspection and process control applications, including data quality, traceability, and consistency across equipment, inspection, and analytics systems. Apply advanced analytics and machine learning techniques to improve inspection throughput and accuracy, process stability and yield, and root-cause identification Support high-volume manufacturing operations by responding to production issues, minimizing downtime, and ensuring automation and inspection systems meet fab performance and reliability requirements. Education & Experience Minimum 5 years' experience in data analytics in semiconductor, materials, or a related industry; or demonstratable equivalent abilities. BS/MS or equivalent degrees in computer science, software engineering, physics, mathematics, statistics or similar STEM field. Skills Leadership capabilities to independently lead complex technical initiatives, provide technical direction in AVI, AI/ML, and automation efforts, and influence cross-functional teams without direct authority. Strong interpersonal, collaboration, and problem-solving skills, with the ability to work effectively in high-pressure manufacturing environments. Experience modeling, analyzing, and validating complex, imperfect real-world manufacturing and inspection datasets, including image and in-situ equipment data. Strong understanding of statistical fundamentals and their application to machine learning, defect detection, process monitoring, and anomaly identification. Solid knowledge of semiconductor manufacturing processes; background in process engineering, materials science, or related natural sciences is a plus. Working Conditions This role is 100% onsite Physical Requirements Ability to sustainably work on a computer full-time. Willingness and ability to work in a cleanroom environment as needed for system integration, testing, or troubleshooting activities. Safety Requirements All employees are required to follow the site EHS procedures and Coherent Corp. Corporate EHS standards. Quality and Environmental Responsibilities Depending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System. Culture Commitment Ensure adherence to company’s values (ICARE) in all aspects of your position at Coherent Corp.: I ntegrity – Create an Environment of Trust C ollaboration – Innovate Through the Sharing of Ideas A ccountability – Own the Process and the Outcome R espect – Recognize the Value in Everyone E nthusiasm – Find a Sense of Purpose in Work Coherent Corp. is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. If you need assistance or an accommodation due to a disability, you may contact us at [email protected] .

Requirements

• Minimum 5 years' experience in data analytics in semiconductor, materials, or a related industry; or demonstratable equivalent abilities.
• BS/MS or equivalent degrees in computer science, software engineering, physics, mathematics, statistics or similar STEM field.
• Leadership capabilities to independently lead complex technical initiatives, provide technical direction in AVI, AI/ML, and automation efforts, and influence cross-functional teams without direct authority.
• Strong interpersonal, collaboration, and problem-solving skills, with the ability to work effectively in high-pressure manufacturing environments.
• Experience modeling, analyzing, and validating complex, imperfect real-world manufacturing and inspection datasets, including image and in-situ equipment data.
• Strong understanding of statistical fundamentals and their application to machine learning, defect detection, process monitoring, and anomaly identification.
• Solid knowledge of semiconductor manufacturing processes

Nice To Haves

• background in process engineering, materials science, or related natural sciences is a plus.

Responsibilities

• Lead the development, deployment, and production support of AI/ML-driven wafer-level and die-level image processing solutions for Automated Visual Inspection (AVI) tools used in front-end and back-end wafer fab operations.
• Design, implement, and sustain advanced vision and image processing pipelines, including Crack detection and advanced defect classification, Die-to-die and wafer-level image stitching, Optical inspection data analysis
• Develop, train, validate, and maintain machine learning models used in AI-powered optical inspection, ensuring robustness, accuracy, and scalability in high-volume manufacturing environments.
• Integrate AI/ML-based solutions with fab automation systems, leveraging in-situ equipment and process data to enable anomaly prediction and early detection for critical processes.
• Work hands-on in the fab environment with automation team members, operations, process engineering, and equipment engineering teams to deploy, debug, and sustain automation, inspection, and process control solutions.
• Ensure reliable data foundations for inspection and process control applications, including data quality, traceability, and consistency across equipment, inspection, and analytics systems.
• Apply advanced analytics and machine learning techniques to improve inspection throughput and accuracy, process stability and yield, and root-cause identification
• Support high-volume manufacturing operations by responding to production issues, minimizing downtime, and ensuring automation and inspection systems meet fab performance and reliability requirements.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level