Lead Engineer, Automation and Application

• 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.

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

• This role is 100% onsite

• 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.:

Integrity – Create an Environment of Trust

Collaboration – Innovate Through the Sharing of Ideas

Accountability – Own the Process and the Outcome

Respect – Recognize the Value in Everyone

Enthusiasm – 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.