Principal AI Data Scientist – Wafer Fabrication - Fremont, CA, United States

Originally posted 9 September 2026 by the employer.

About the role

This role involves analyzing datasets from wafer fabrication processes to understand process behavior, variation, and performance, and supporting the ramp of new products at the site.

What you'll do

• Analyze datasets generated by wafer fabrication processes, equipment, sensors, metrology systems, and manufacturing execution systems.
• Apply statistical analysis, AI, machine learning, and data-mining techniques for process monitoring, anomaly detection, wafer and lot excursion analysis, yield analysis and prediction, and root-cause investigation.
• Integrate data from multiple sources, including process recipes, equipment logs, sensor data, metrology results, defect inspection, and production history.
• Develop reusable data pipelines, analytical tools, dashboards, and model-monitoring methods.
• Support design of experiments, process characterization, and continuous improvement activities.
• Help establish best practices for data quality, feature engineering, model validation, documentation, and responsible use of AI in development and manufacturing.

What you'll need

• Minimum of 5 years of experience with AI, preferably including ML, and statistical analytic techniques.
• Bachelor’s degree in Data Science, Engineering, Science, Computer Science or Mathematics.
• Professional experience applying machine learning, artificial intelligence, advanced statistics, and data science to real-world engineering or manufacturing problems.
• Experience with SQL and modern data-processing or data-platform technologies.
• Strong knowledge of statistical methods, experimental design, regression, classification, clustering, anomaly detection, and model evaluation.
• Programming skills in Python and experience with common data-science and machine-learning libraries.
• Experience working with structured, time-series, sensor, or high-volume manufacturing data.

Nice to have

• Master’s degree.
• Experience in AI/ML model deployment through RESTful APIs, containerization, and container orchestration.
• Experience with cloud-based ML training and inference using AWS, GCP, Azure, or Databricks.
• Exposure to wafer fabrication, photonics, and telecommunications.
• Ability to work collaboratively with domain experts and explain complex analytical results in practical engineering terms.
• Demonstrated ability to take an analysis from problem definition through deployment, validation, and communication of results.

Skills: AI, machine learning, wafer fabrication, yield analysis, process monitoring, Python