Staff AI Data Engineer — Wafer Analytics & ML Pipelines

Coherent Corp.; Fremont (CA); On-site; USD 110,000 - 180,000; Full time

Job summary

Coherent Corp. is seeking a data scientist specializing in ML/AI for on-site work in California. You will analyze complex fabrication datasets, apply advanced statistics, and develop data pipelines and dashboards to guide process improvements.

You will collaborate with engineering and manufacturing teams to interpret results, distinguish correlation from causation, and deploy models via APIs and containerized environments. Prior experience with wafer-related data is a plus.

Qualifications

• Minimum 2 years of professional experience applying ML/AI to engineering or manufacturing problems.
• Bachelor’s degree in Data Science, Engineering, Science, CS or Mathematics required; Master’s preferred.

Responsibilities

• Analyze datasets from wafer fabrication processes, equipment, sensors, metrology systems, and MES.
• Drive forward detailed data analysis across multiple projects using ML/AI tools.
• Apply statistics, AI, ML, and data-mining for device understanding, process monitoring, anomaly detection, and yield analysis.
• Collaborate with teams using AI/ML and integrate data from various sources.
• Translate results into engineering insights and actionable recommendations.
• Develop reusable data pipelines, tools, dashboards, and model monitoring.
• Support DOE, process characterization, and continuous improvement activities.
• Establish best practices for data quality, feature engineering, model validation, and responsible AI use.

Skills

ML & AI

Data analysis

Team collaboration

Large datasets

SQL

Python

AI deployment

Time-series data

Cloud ML

Wafer fabrication exposure

Education

Bachelor's degree in DS/Engineering/CS/Math

Master's degree preferred

Tools

SQL

Python

RESTful APIs

Containerization

Docker

Kubernetes

Databricks

AWS

GCP

Job description

Coherent Corp. is seeking a data scientist specializing in ML/AI for on-site work in California. You will analyze complex fabrication datasets, apply advanced statistics, and develop data pipelines and dashboards to guide process improvements.

You will collaborate with engineering and manufacturing teams to interpret results, distinguish correlation from causation, and deploy models via APIs and containerized environments. Prior experience with wafer-related data is a plus.