AI ML Data Engineer

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

The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT’s mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.

Job Description/Preferred Qualifications

Role

You will be part of a cutting-edge team working on Large Language Models (LLMs), Machine Learning, Deep Learning, and Retrieval-Augmented Generation (RAG) pipelines. You’ll help design, build, and evaluate AI systems that solve complex real-world problems at scale.

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Key Responsibilities

• Develop and optimize RAG pipelines: document chunking, embedding generation, vector storage, retrieval, reranking, and grounded generation with citations.
• Work on LLM-based applications: fine-tuning open-source models (LLaMA, Mistral, etc.), building prompt strategies, and deploying inference services.
• Contribute to machine learning models (classification, regression, recommendation, anomaly detection) and deep learning architectures (CNNs, RNNs, Transformers).
• Implement robust model evaluation frameworks (accuracy, F1, BLEU, perplexity, hallucination detection, relevance).
• Collaborate with senior engineers on scalable pipelines, guardrails, and integration with enterprise systems.
  
  
  

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Required Skills

• Programming & Foundations
• Strong in Python, data structures, and algorithms.
• Hands-on with NumPy, Pandas, Scikit-learn for ML prototyping.
• Machine Learning
• Understanding of supervised/unsupervised learning, regularization, feature engineering, model selection, cross-validation, ensemble methods (XGBoost, LightGBM).
• Deep Learning
• Proficiency with PyTorch (preferred) or TensorFlow/Keras.
• Knowledge of CNNs, RNNs, LSTMs, Transformers, Attention mechanisms.
• Familiarity with optimization (Adam, SGD), dropout, batch norm.
• LLMs & RAG
• Hugging Face Transformers (tokenizers, embeddings, model fine-tuning).
• Vector databases (Milvus, FAISS, Pinecone, ElasticSearch).
• Prompt engineering, function/tool calling, JSON schema outputs.
• Data & Tools
• SQL fundamentals; exposure to data wrangling and pipelines.
• Git/GitHub, Jupyter, basic Docker.
  
  
  

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Nice to Have

• Built a personal ML/LLM project (chatbot, RAG app, document Q&A, finetuned model).
• Familiarity with LangChain/LlamaIndex/Agno frameworks.
• Knowledge of cloud platforms (Azure/AWS/GCP) and MLOps basics (CI/CD, MLflow, W&B).
• Exposure to knowledge graphs or multi-agent workflows.
  
  
  

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What We’re Looking For

• Solid academic foundation with strong applied ML/DL exposure.
• Curiosity to learn cutting-edge AI and willingness to experiment.
• Clear communicator who can explain ML/LLM trade-offs simply.
• Strong problem-solving and ownership mindset.
  
  
  

Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.

KLA is proud to be an equal opportunity employer

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