Intern will analyze semiconductor backend test processes and equipment performance, evaluate new technologies for high-volume manufacturing, identify yield, quality, reliability, cycle-time, and cost improvements, and apply structured problem-solving, risk assessment, FMEA, data analysis, and responsible AI methods. Deliverables include baseline analyses, performance trend findings, qualification summaries, recommendations, technical reports, presentations, and potentially an AI-enabled proof of concept.

Intern will assess manufacturing site conditions and strategic layouts, collaborate with Manufacturing, Engineering, Facilities, and Tool Owners, analyze planning data, and develop automation, dashboards, or data-management solutions using Python, Power Automate, SQL, and AI-enabled tools. The project focuses on improving layout feasibility assessment, reporting, information organization, and planning workflow efficiency.

Manage the lifecycle of software applications supporting automated semiconductor manufacturing. Analyze business and technical requirements, develop secure solutions, oversee testing and releases, apply patches, monitor systems, prevent downtime, and provide technical guidance. The role also involves end-user training, collaboration with global IT teams, software project management, Agile development, and adoption of AI-powered tools to improve delivery and operational efficiency.