Job Description

Join the BBP Algorithm team at KLA as a Summer Intern to advance AI/ML models for defect detection in optical patterned wafer inspection systems, focusing on improving sensitivity and throughput in semiconductor manufacturing.

Requirements

Currently pursuing MS or PhD in Computer Science, Electrical/Computer Engineering, Mathematics, Physics, or related field (exceptional BS candidates considered)
Hands-on experience training deep learning models for vision (classification, detection, segmentation, or anomaly)
Strong foundations in linear algebra, probability/statistics, and optimization
Proficiency with Python and modern DL frameworks (PyTorch or TensorFlow) on Linux
Solid software fundamentals (Git, testing, code review)

Responsibilities

Advance AI/ML models for defect detection, classification, and anomaly discovery on real wafer imagery
Curate and engineer datasets to maximize label efficiency and generalization across layers, technologies, and tools
Train, evaluate, and iterate using modern deep learning frameworks
Prototype algorithmic ideas and transition the best candidates into production-quality code
Optimize for scale and speed to meet on-tool and near-real-time constraints
Collaborate cross-functionally with system engineering and software teams