Senior​/Lead Engineer

Primary Duties & Responsibilities

• Identify, prioritize, and collaborate with cross-functional engineering teams on AI/ML, Factory Automation, APC, and FDC projects that deliver the highest operational impact and return on investment (ROI) across the wafer fabrication facility.
• Develop, deploy, maintain, and enhance AI/ML applications, Factory Automation solutions, Advanced Process Control (APC) controllers, and Fault Detection & Classification (FDC) models to improve yield, process stability, equipment performance, throughput, and overall manufacturing efficiency.
• Collect, integrate, and analyze manufacturing data generated through Factory Automation, APC, FDC, MES, process tools, metrology systems, equipment sensors, and manufacturing databases.
• Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines and data engineering workflows to acquire, cleanse, transform, and integrate manufacturing data for advanced analytics, machine learning, and intelligent manufacturing applications.
• Develop machine learning models and advanced analytics solutions for yield prediction, process optimization, anomaly detection, predictive maintenance, equipment health monitoring, process drift detection, root cause analysis, and intelligent process control.
• Design and implement predictive analytics, dashboards, and decision-support applications that enable proactive identification of manufacturing issues and data-driven decision making.
• Translate process engineering requirements and customer requests into integrated AI/ML, automation, APC, and FDC solutions for specific process tools, process areas, and fab-wide optimization initiatives.
• Support semiconductor equipment integration using SECS/GEM communication standards, Manufacturing Execution Systems (MES), and factory automation infrastructure.
• Support new equipment installations, product introductions, and process technology transfers by implementing robust automation, APC/FDC, and AI/ML solutions.
• Troubleshoot and resolve automation, APC, FDC, data integration, database, and equipment communication issues to ensure reliable manufacturing operations.
• Collaborate with Process, Equipment, Manufacturing, Yield Enhancement, and IT teams to deploy intelligent manufacturing solutions and continuously improve yield, throughput, cycle time, equipment effectiveness (OEE), and engineering productivity.

• Minimum 5 years' experience in data analytics in semiconductor, materials, or a related industry; or demonstratable equivalent abilities.
• BS/MS or equivalent degree 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.