Teams at KLA

Design and implement ML, statistical, and deep learning models (classification, anomaly detection, segmentation, forecasting) and agentic AI/LLM systems for semiconductor manufacturing. Build production-quality C++ and Python software, integrate LLMs and RAG pipelines, evaluate model performance, collaborate across engineering and product teams, and support deployment and customer adoption.

Curate, govern, and optimize structured knowledge assets across their full lifecycle. The role improves content findability, reuse, metadata quality, taxonomy, and information architecture while preparing content for AI-powered search and knowledge retrieval. Responsibilities include auditing content, identifying duplication, supporting modularization, monitoring content health metrics, and partnering with technical writers, information architects, engineers, and product teams on scalable governance and transformation initiatives.

Develop and debug software using C#, C++, Angular, and .NET for semiconductor inspection systems. Participate in the full software development lifecycle, including requirements, design, development, deployment, support, and service. Collaborate with global cross-functional teams and acquire expertise in inspector software and defect inspection use cases. Apply clean-code and software engineering best practices while supporting technical discussions and occasional customer or site visits.