AI-Driven Electrical Yield Failure Analysis Engineer

3000 Micron Idaho Semiconductor Manufacturing (Triton) LLC

Boise (ID)

On-site

USD 120,000 - 150,000

Full time

3 days ago

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Benefits offered by this job

Medical, Dental & Vision plans

Paid time off

Paid holidays

Job summary

Micron Technology is seeking an Yield Enhancement Electrical Failure Analysis Engineer to investigate electrical failures, drive yield improvement, and deliver data‑driven insights. You will perform hands‑on electrical characterization, implement AI‑assisted workflows, and collaborate with Design, Process, Product Engineering, Test, Manufacturing, and Data Science teams.

The role emphasizes developing automated analysis tools, AI‑driven reporting, and robust technical documentation to accelerate

Qualifications

Bachelor's or master's degree in Electrical Engineering, Computer Engineering, Materials Science, Computer Science, Data Science, or Chemical Engineering.
Ability to apply knowledge of semiconductor devices, process integration, memory architecture, and device operation to analyze electrical failures and yield issues.
Ability to perform electrical and failure analysis as defined by area skill guidelines.
Experience conducting advanced data analysis, statistical evaluation, and data visualization to support yield investigations and failure analysis results.
Proficiency with data analytics, scripting, automation, or programming tools (e.g., Python, SQL, JMP, Power BI, Tableau, or equivalent).
Ability to leverage AI tools, large language models, and automation technologies to improve data processing, engineering productivity, investigation efficiency, and technical reporting.
Ability to summarize investigation findings, including potential root cause and recommended actions, in a concise and technically sound report.
Ability to operate lab equipment safely and perform required tasks and basic troubleshooting.

Responsibilities

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.
Develop and maintain yield monitoring methodologies, screening strategies, defect classification systems, and AI‑assisted detection models.
Partner with Design, Process Integration, Product Engineering, Test, Manufacturing, and Data Science teams to resolve yield and reliability issues.
Develop, automate, and maintain data analysis tools, dashboards, reporting systems, and AI‑powered workflows to improve investigation efficiency.
Apply AI, machine learning, statistical methods, and advanced analytics techniques to accelerate defect identification and yield trending.
Leverage generative AI and knowledge‑management tools to accelerate technical reviews and information retrieval.
Lead technical reviews and communicate investigation results, risks, and recommendations to stakeholders.
Create and maintain technical documentation, best practices, training materials, and AI prompt libraries.
Evaluate and implement new electrical characterization, debug methodologies, automation solutions, and AI‑enabled FA techniques.
Support NPI, qualification activities, and technology transfers by providing yield analysis and data‑driven risk assessments.
Identify opportunities for process improvement and productivity through automation and AI adoption.