Intern, Machine Learning – Semiconductor Laser Manufacturing (Summer 2026)

Coherent Corp. • Fremont, CA

1d • Onsite

About The Position

We are seeking a highly motivated Machine Learning Intern to join our
Semiconductor Laser Engineering team for Summer 2026. In this role, you will
apply machine learning techniques to improve semiconductor laser manufacturing
yield, optimize diode laser screening methods and inverse engineer for better
performance. You will work closely with process engineers, device engineers, and
data scientists to develop models that enhance process control and product
performance prediction in a high-volume manufacturing environment.

Requirements

• Education Level Required: Bachelor's / Master’s / PhD
• Majors: Computer Science, Electrical Engineering, Applied Physics, Materials Science, Data Science, Statistics, Applied Mathematics, or related technical discipline
• Relevant coursework or extracurricular experience in machine learning, statistics, data analytics, semiconductor devices, solid-state physics, or manufacturing process analysis is a plus.
• Experience with programming (Python preferred), data analysis, and machine learning frameworks through coursework, research projects, or internships is highly desirable.
• Open to currently enrolled students or those who have graduated within one year of the internship start date.
• Strong programming skills in Python (NumPy, Pandas, scikit-learn, PyTorch or TensorFlow preferred)
• Understanding of machine learning fundamentals (supervised and unsupervised learning)
• Familiarity with statistical methods and experimental design
• Experience with data visualization tools (Matplotlib, Seaborn, etc.)
• Ability to work with large datasets and perform feature engineering
• Excellent written and verbal communication skills
• Team-oriented but capable of independent technical work
• Attention to detail in data analysis and model validation

Nice To Haves

• Experience with semiconductor test data or manufacturing datasets
• Knowledge of DOE (Design of Experiments), SPC, or yield analysis
• Familiarity with SQL or manufacturing database systems

Responsibilities

• Analyze large-scale manufacturing and test datasets to identify yield drivers and performance trends in semiconductor laser production
• Develop and evaluate machine learning models to:   Predict device performance and reliability Identify root causes of yield loss Improve wafer-level and die-level screening strategies
• Design data preprocessing and feature engineering pipelines for manufacturing and parametric test data
• Apply statistical analysis and ML techniques (e.g., regression, classification, clustering, anomaly detection) to optimize diode laser screening thresholds
• Collaborate with device, process, and test engineers to translate model insights into actionable manufacturing improvements
• Validate model performance using historical production data and controlled experiments
• Present findings, technical insights, and recommendations to engineering leadership
• Deliver a final technical report and presentation summarizing methodology, results, and potential production implementation roadmap

What This Job Offers

• Career Level: Intern