Specialist, AI Engineer
KLA Corporation (company site, opens in a new tab)8+ yrsChennaiOn-siteDirect career pageEst. 30–55 LPA
Posted on 3 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and prototype machine learning and deep learning models for semiconductor manufacturing processes using Python and ML frameworks like PyTorch or TensorFlow.
- Implement and optimize advanced AI techniques including CNNs, RNNs, Transformers, and work with large language models (LLMs) integrating vector databases and prompt engineering.
- Collaborate across teams to apply AI solutions for wafer surface quality and defect inspection, impacting yield analysis and semiconductor fabrication monitoring.
Minimum Requirements
- Doctorate degree with 5 years, Master's degree with 8 years, or Bachelor's degree with 7 years of experience in building AI systems/solutions involving Machine Learning, Deep Learning, and LLMs.
- Strong proficiency in Python programming, data structures, algorithms, and machine learning libraries such as NumPy, Pandas, and Scikit-learn.
- Experience with ML frameworks (PyTorch or TensorFlow), familiarity with Hugging Face Transformers, vector databases (Milvus, FAISS, Pinecone, ElasticSearch).
- Knowledge of SQL, data wrangling, Git/GitHub, Jupyter, and basic Docker usage.
Ideal Candidate Profile
- Experienced AI/ML engineer with a deep understanding of applied machine learning and deep learning techniques specifically for industrial semiconductor processes.
- Able to manage end-to-end AI solution development including prototyping, model tuning, and integration with state-of-the-art LLM and vector search technologies.
- Strong communicator capable of explaining complex ML and LLM concepts and trade-offs clearly to multidisciplinary teams, with a problem-solving and ownership-oriented approach.