About the role
AI summarisedJoin Micron Technology to drive AI transformation within semiconductor Product Engineering. This role involves developing and deploying advanced predictive and diagnostic Machine Learning models on large-scale semiconductor datasets to optimize yield, reduce test time, and enhance product reliability.
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Key Responsibilities
- Apply advanced ML techniques on large-scale structured semiconductor datasets, including wafer fab inline data, probe data, and test data.
- Build, validate, and maintain end-to-end ML workflows supporting NPI and HVM decision-making.
- Design and implement agentic AI solutions to automate Product Engineering workflows (e.g., Yield/reliability analysis, test program validation, report generation).
- Integrate AI agents with enterprise and engineering systems (e.g., JIRA, Confluence, SharePoint).
- Collaborate with Fab, NAND Technology Development, and Quality/Reliability teams to address failures and drive data-backed technical decisions for NAND product releases.
- Mentor Citizen Data Scientists on applying machine learning techniques to solve real engineering problems and build structured learning paths.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical/Electronic Engineering.
- Minimum 4 years of experience in ML/AI.
- Strong proficiency in Python and data processing libraries (Pandas, NumPy, Scikit-learn).
- Hands-on experience with ML models for structured/tabular data, including regression, tree-based models, and gradient boosting.
- Ability to build, evaluate, and interpret ML models for engineering decision-making.
- Strong analytical and problem-solving skills.
- Excellent communication skills to translate data insights into engineering actions.