Staff AI Data Engineer – Wafer Fabrication

Location: Fremont, CA, United States

Primary Duties & Responsibilities

• Analyze datasets generated by wafer fabrication processes, equipment, sensors, metrology systems, and manufacturing execution systems.
• Support multiple projects and drive forward detailed data analysis employing various ML/AI tools
• Apply statistical analysis, AI, machine learning, and data-mining techniques for:
  • Deeper understanding of devices and fabrication processes.
  • Process monitoring and anomaly detection
  • Wafer and lot excursion analysis
  • Yield analysis and prediction
  • Root-cause investigation
• Collaborate with others using AI & ML
• Integrate data from multiple sources, including process recipes, equipment logs, sensor data, metrology results, defect inspection, and production history.
• Translate analytical results into clear engineering insights and actionable recommendations.
• Communicate these findings to engineers and managers.
• Work with engineers to distinguish correlation from likely physical or process-driven causation.
• 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.

 

Education & Experience

• The Candidate will have a minimum of 2 years of experience with AI, preferably including ML, preferably with experience in statistical analytic techniques. 

• A Bachelor’s degree in Data Science, Engineering, Science, Computer Science or Mathematics is required, a Master’s degree is preferred.

Skills

The candidate will have competency in several of the following areas:

• Minimum two years of professional experience applying machine learning, artificial intelligence, and data science to real-world engineering or manufacturing problems. 
• Demonstrated ability to work simultaneously on multiple projects, in detail.
• Demonstrated ability to work in teams involving members from Engineering, Manufacturing, MES Data Systems and AI/ML, with the ability to explain complex analytical results in practical engineering terms.
• Experience with handling large data sets in agentic AI/ML.
• Experience with SQL and modern data-processing or data-platform technologies.
• Programming skills in Python and experience with common data-science and machine-learning libraries.
• Experience in AI/ML model deployment through RESTful APIs, containerization, and container orchestration.
• Experience working with structured, time-series, sensor, or high-volume manufacturing data.
• Basic knowledge of statistical methods, experimental design, regression, classification, clustering, anomaly detection, and model evaluation.
• Experience with cloud-based ML training and inference using AWS, GCP, Azure, or Databricks is a plus.
• Exposure to wafer fabrication, photonics, and telecommunications is a plus.
• Demonstrated ability to take small projects from problem definition through deployment, validation, and communication of results.

Working Conditions

The job is on-site for the first three months, with the possibility to convert to hybrid afterwards. The job requires weekly morning hours and occasional evening and weekend hours. Travel to other Coherent sites in the Bay Area and the US may be possible to share knowledge with other experts.

Physical Requirements

• Sitting or standing several hours per day, with the option of having a sit-stand desk.
• Extensive keyboard and mouse work.

Safety Requirements

 

All employees are required to follow the site EHS procedures and Coherent Corp. Corporate EHS standards.

Quality and Environmental Responsibilities

 

Depending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System.

Culture Commitment

Ensure adherence to company’s values (ICARE) in all aspects of your position at Coherent Corp.:

Integrity – Create an Environment of Trust

Collaboration – Innovate Through the Sharing of Ideas

Accountability – Own the Process and the Outcome

Respect – Recognize the Value in Everyone

Enthusiasm – Find a Sense of Purpose in Work

Coherent Corp. is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.

About Us

Coherent is a global leader in lasers, engineered materials and networking components. We are a vertically integrated manufacturing company that develops innovative products for diversified applications in the industrial, optical communications, military, life sciences, semiconductor equipment, and consumer markets. Coherent provides a comprehensive career development platform within an environment that challenges employees to perform at their best, while rewarding excellence and hard-work through a competitive compensation program. It's an exciting opportunity to work for a company that offers stability, longevity and growth. Come Join Us!

Note to recruiters and employment agencies: We will not pay for unsolicited resumes from recruiters and employment agencies unless we have a signed agreement and have required assistance, in writing, for a specific opening.


Job Summary: We are seeking an AI and machine learning professional to analyze data from wafer fabrication processes and help deepen our understanding of process behavior, variation, and performance. Our site is rapidly ramping and introducing new products, and this opportunity provides broad exposure to Development, Engineering, Manufacturing and Process Teams. You will implement larger AI/ML projects under guidance and independently execute smaller analyses and automation efforts. The ideal candidate combines strong experience in AI/ML and data analysis with an interest in semiconductor wafer fabrication.