Lead Engineer, Automation and Application

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 an...