Principal AI Data Scientist – Wafer Fabrication
Fremont, CA, United States
- Pay
- Salary not listed in the saved posting
- Work setup
Hybrid stated — work setup source
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
Read the full posting- Employment
- Unconfirmed
What you’ll bring
All qualificationsCore experience
- 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.
- 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.
- 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.
Preferred experience
- Experience with cloud-based ML training and inference using AWS, GCP, Azure, or Databricks is a plus.
Qualification wording
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.
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.
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.
Experience with cloud-based ML training and inference using AWS, GCP, Azure, or Databricks is a plus.
Education & alternatives
- 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
Tools in this posting
- Python
- SQL
- AWS
- Azure
- Databricks
- Google Cloud (GCP)
Source — Tool mentions in context
- 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.
- 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.
- 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.
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.:
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.
If you need assistance or an accommodation due to a disability, you may contact us at talentacquisition@coherent.com.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on hcwp.fa.us2.oraclecloud.com. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Fremont, CA, United States
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
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Sep 10, 2026
- Recorded sightings
- 88
- Last seen by us
- Oct 9, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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