Intern, Machine Learning – Semiconductor Laser… at II-VI… · 41762…

Summary: II-VI Aerospace & Defense is seeking a highly motivated Machine Learning Intern to join their Semiconductor Laser Engineering team for Summer 2026. The role involves applying machine learning techniques to improve semiconductor laser manufacturing yield and collaborating with engineers to enhance process control and product performance prediction. 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 Required Qualifications: - 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 Preferred Qualifications: - 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 Required Skills: Machine Learning, Python, Data Analysis Important Skills: Statistical Methods, Data Visualization Nice-to-Have Skills: Feature Engineering, SQL Internship Start Date: Start in 2026 Summer