Principal Product Engineer - AI/ML & Advanced Data Analytics Lead (HBM)

About the role

Micron is hiring a Principal Product Engineer as AI/ML and Advanced Data Analytics Lead within its Heterogeneous Integration Group (HIG) HBM Product Engineering organization. You will lead a team of engineers building the predictive models that determine how HBM is screened, dispositioned and tested in high-volume manufacturing, and work with cross-functional teams to prototype, build and scale AI-driven solutions that improve quality, cost, cycle time and engineering efficiency.

Key responsibilities

• Mentor and develop team members, and lead a team of engineers by setting technical direction, reviewing modeling work, balancing workload and hiring and onboarding.
• Own the design, training, validation and productization of models that predict yield loss, defect escapes and reliability risk, using gradient-boosted trees, time-series models, anomaly detection and classical statistics.
• Build and operate the deployment path, including real-time and batch inference, performance monitoring, drift detection, retraining triggers, feature change management and rollback.
• Develop and productionize machine learning and deep learning models for classification, regression, anomaly detection, failure analysis and engineering decision support.
• Build scalable data pipelines and analytical workflows, and apply Python, SQL and data science libraries (e.g. pandas, matplotlib) to analyze large, heterogeneous datasets.
• Use distributed processing frameworks (e.g. PySpark, BigQuery) for data cleansing, outlier detection and missing-data handling.
• Support deployment, monitoring and operationalization of AI/ML solutions in cloud and enterprise environments.
• Apply GenAI and agentic systems to failure triage, root-cause analysis, knowledge retrieval, data extraction, code generation and analysis automation.
• Collaborate with Product, Test, Yield, Process and Fab teams, and communicate technical findings to technical and non-technical stakeholders.

Required profile

• Bachelor's or Master's degree in Electrical Engineering, Computer Science, Data Science, Statistics, AI or a related field.
• At least 5 years of hands-on machine learning, data science or predictive modeling experience, including at least 2 years leading a team of engineers or data scientists.
• Demonstrated depth in gradient-boosted tree methods (XGBoost, LightGBM, CatBoost) and time-series modeling, with models running in production.
• Ability to define business-level acceptance criteria for models and strong communication skills.
• Preferred: semiconductor manufacturing, yield prediction, memory products, advanced packaging or heterogeneous integration experience.

Required skills

• Python and SQL
• Pandas, scikit-learn, matplotlib, plotly
• PySpark, BigQuery
• GCP, AWS or Azure