New College Grad - Yield Enhancement Electrical Failure Analysis Engineer

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Department Intro The Yield Enhancement organization partners closely with Fab and Yield Engineering teams to monitor manufacturing performance, investigate defect issues, and drive yield improvement through detailed electrical and failure analysis.

Overview The Yield Enhancement Electrical Failure Analysis Engineer performs investigative electrical failure analysis to identify, categorize, and resolve defect issues impacting yield. This role combines hands-on electrical characterization, advanced data analytics, automation, and AI-enabled engineering workflows to accelerate defect detection, root cause identification, and yield improvement. The engineer monitors manufacturing performance, prioritizes yield-related investigations, and delivers data-driven insights and clear reporting to support business decisions and continuous improvement.

Perform electrical and failure analysis in alignment with defined area skill guidelines and summarize findings using clear, data-driven reporting and AI-assisted documentation tools. Operate and support lab equipment while adhering to safety guidelines and supporting department and company objectives. Drive root cause investigations by correlating electrical test data, FA results, process information, manufacturing history, and AI-generated insights to identify yield detractors and recommend corrective actions. Develop and maintain yield monitoring methodologies, screening strategies, defect classification systems, and AI-assisted detection models to improve excursion response and defect identification accuracy. Partner with Design, Process Integration, Product Engineering, Test, Manufacturing, and Data Science teams to resolve yield and reliability issues and drive product quality improvements. Develop, automate, and maintain data analysis tools, dashboards, reporting systems, and AI-powered workflows to improve investigation efficiency and reduce manual data processing. Apply AI, machine learning, statistical methods, and advanced analytics techniques to accelerate defect identification, yield trending, anomaly detection, predictive analysis, and root cause determination. Leverage generative AI and knowledge-management tools to accelerate technical reviews, investigation planning, report generation, and information retrieval. Lead technical reviews and communicate investigation results, risks, recommendations, and data-driven insights to cross-functional stakeholders and management. Create and maintain technical documentation, best practices, training materials, AI prompt libraries, and knowledge-sharing resources for the organization. Evaluate and implement new electrical characterization, debug methodologies, automation solutions, and AI-enabled FA techniques to improve problem-solving capability. Support new product introduction (NPI), qualification activities, and technology transfers by providing yield analysis, failure investigation expertise, and data-driven risk assessments. Identify opportunities for process improvement, cost reduction, cycle-time reduction, and productivity enhancement through automation, AI adoption, and workflow optimization. Provide technical mentorship and training to engineers and technicians on semiconductor device operation, failure mechanisms, data analytics, AI-assisted engineering tools, and debug methodologies. Champion AI-enabled ways of working by identifying, evaluating, and implementing emerging technologies that improve engineering productivity, technical insight generation, and decision-making. Manage and prioritize multiple investigations simultaneously while ensuring timely communication of critical findings and