• Leverage AI-enabled and AI-assisted work methods, including Microsoft Copilot, Generative AI, and advanced analytics tools, to improve equipment utilization, yield performance, alarm code analysis, parts lifetime prediction, and manufacturing efficiency.
• Utilize AI-powered data analysis to identify equipment performance gaps, predict equipment failures, optimize preventive maintenance strategies, and reduce unplanned downtime.
• Apply AI-assisted troubleshooting techniques to accelerate root cause analysis of equipment alarms, process excursions, and yield loss mechanisms.
• Familiar with TCB/DB process and possesses a minimum of 5 years of semiconductor equipment engineering experience.
• Identify, diagnose, and resolve assembly equipment related issues utilizing data-driven and AI-supported methodologies.
• Coordinate and execute process, equipment, and material evaluations, leveraging AI insights to optimize manufacturing performance and quality.
• Lead and participate in utilization improvement, yield enhancement, cost reduction, and smart manufacturing initiatives through automation and AI technologies.
• Validate and qualify new processes, equipment, materials, and manufacturing technologies for NPI deployment.
• Support FDC/RMS/APC/SPC systems and utilize AI-driven analytics to identify trends, abnormalities, and improvement opportunities.
• Drive site-to-site best practice transfer and digital transformation initiatives.
• Manage supplier quality and risk mitigation activities through data analytics and predictive monitoring techniques.
• Support internal and external audits while maintaining compliance with engineering and quality standards.
• Demonstrate effective adoption of Microsoft Copilot and other AI technologies to enhance engineering productivity, knowledge management, documentation generation, decision making, and operational excellence.