Company Overview

KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.

Group/Division

With over 40 years of semiconductor process control experience, chipmakers around the globe rely on KLA to ensure that their fabs ramp next-generation devices to volume production quickly and cost-effectively. Enabling the movement towards advanced chip design, KLA's Global Products Group (GPG), which is responsible for creating all of KLA’s metrology and inspection products, is looking for the best and the brightest research scientist, software engineers, application development engineers, and senior product technology process engineers. The Broadband Plasma Division (BBP) provides market-leading patterned wafer optical inspection systems for leading-edge IC manufacturing. Logic, foundry, and memory customers depend on BBP products to detect yield-critical defects for process debug and excursion monitoring at advanced process nodes. BBP flagship products include the 29xx and 39xx series which leverage Broadband Plasma technology to capture a wide range of defects with ultimate sensitivity at the optical inspection speeds needed for inline defect monitoring.

Job Description/Preferred Qualifications

Team: Algorithm — Broadband Plasma Wafer Inspection (BBP)
Type: Full-time Internship (Summer preferred; start date flexible)
Location: Milpitas, CA (on-site)

Why this role

Join the BBP Algorithm team that powers some of the world’s most advanced optical patterned wafer inspection systems. You’ll help push the state of the art in computer vision and deep learning to detect yield-limiting defects—improving sensitivity, robustness, and throughput on production tools used in leading fabs.

What you’ll do

• Advance AI/ML models for defect detection, classification, and anomaly discovery on real wafer imagery; design experiments, define metrics, and drive SOTA baselines forward.
• Curate and engineer datasets (balancing/partitioning, augmentation strategies, labeling guidance) to maximize label efficiency and generalization across layers, technologies, and tools.
• Train, evaluate, and iterate using modern deep learning frameworks; build repeatable pipelines for preprocessing, training, inference, and reporting.
• Prototype algorithmic ideas (e.g., semi/self-supervised learning, domain adaptation, uncertainty estimation, active learning) and transition the best candidates into production-quality code.
• Optimize for scale and speed (efficient ops, quantization/pruning, GPU utilization) to meet on-tool and near-real-time constraints.
• Collaborate cross-functionally with system engineering and software teams on integration, testing, and demo/beta evaluations; contribute to documentation and quality practices.

Minimum Qualifications

• 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; ability to analyze complex, noisy data.
• Proficiency with Python and modern DL frameworks (PyTorch or TensorFlow) on Linux; solid software fundamentals (Git, testing, code review).

Preferred Qualifications

• Knowledge of image processing / computer vision beyond DL (filters, registration, morphology, feature engineering).
• Experience with C++ in Linux/Windows and/or CUDA/GPU acceleration; familiarity with performance profiling and memory optimization.
• Exposure to MLOps practices (experiment tracking, model/data versioning, reproducible pipelines).
• Background or i