About the job
Core
Operating and managing semiconductor wafer manufacturing utility equipment (mechanical, UPW, Chemical), utilizing AI data analytics for predictive maintenance and efficiency improvements.
Role type
Semiconductor Utility Equipment Engineer (AI/Data Analytics focus)
Builds
Stable utility supply systems, predictive maintenance frameworks, and digitalized equipment management tools for semiconductor wafer fabs.
Domain
Semiconductor manufacturing / Industrial Utilities / AI Data Analytics
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Mechanical/Chemical engineering principles, data-driven problem solving, AI data analytics application, logical root cause analysis, sensor/monitoring data utilization, statistical data analysis, Python, data visualization tools, generative AI tools.
Preferred skills
Cross-domain expertise in mechanical/UPW/Chemical utilities, prior experience integrating AI data technologies into equipment management, data-related certifications.
Technologies
Python, Excel, Data visualization tools, Generative AI tools, Sensor/Monitoring systems
Responsibilities
Analyze operating status and manage anomalies in utility equipment, improve efficiency and troubleshoot via data analysis, build predictive maintenance systems using AI data, collect and visualize equipment operation data for digitalization, analyze energy usage and identify savings opportunities, support technical review/design/construction/commissioning for new equipment investments, establish and advance equipment standards and preventive maintenance systems.
Seniority
Mid-level to Senior, hands-on IC
