Job description

Primary Duties & Responsibilities • 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: • 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 5 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: • Several years of 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 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 is a plus. • Experience working with structured, time-series, sensor, or high-volume manufacturing data. • Exposure to wafer fabrication, photonics, and telecommunications is a plus. • 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. 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.: I ntegrity – Create an Environment of Trust C ollaboration – Innovate Through the Sharing of Ideas A ccountability – Own the Process and the Outcome R espect – Recognize the Value in Everyone E nthusiasm – 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. If you need assistance or an accommodation due to a disability, you may contact us at talentacquisition@coherent.com . Job Summary: We are seeking an experienced 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 develop analytical and machine learning methods that help explain process outcomes, detect anomalies, identify root causes, improve process control, and support data-driven engineering decisions. The ideal candidate combines strong experience in AI/ML and data analysis with an interest in semiconductor wafer fabrication.

Requirements

Must-haves

Primary Duties & Responsibilities
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:
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 5 years of experience with AI, preferably including ML, preferably with experience in statistical analytic techniques.
The candidate will have competency in several of the following areas:
Several years of 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.

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlsqlpythonawsgcpazure

Platform: oracle-cloud
Effort: medium