- Location
- IND-Tamil Nadu-Chennai-KLA, India
- Type
- Full-time
- Department
- IT
- Education
- PhD
- Source
- Workday
Description
Company Overview
Group/Division
Job Description/Preferred Qualifications
About the Role
We are looking for an AI Engineer to design and develop machine learning, statistical analytics, and agentic AI solutions for semiconductor manufacturing and engineering applications. The role combines software engineering, applied machine learning, deep learning, computer vision, and modern AI frameworks to build intelligent systems that improve product performance, defect detection, engineering productivity, and manufacturing insights.
The engineer is expected to contribute independently, lead small to medium-sized technical initiatives, and collaborate across software, algorithms, systems, data science, and product teams. Given the product is a large data analytics solution for the semi industry, proficiency in C++ is necessary in addition to python.
Key Responsibilities
Machine Learning & Statistical Analytics
- Design and implement machine learning solutions for classification, regression, clustering, anomaly detection, and forecasting.
- Develop statistical models using:
- Hypothesis testing
- Regression analysis
- Bayesian methods
- PCA
- Time-series analysis
- Design of Experiments (DOE)
- Predictive analytics
- Analyze large-scale manufacturing and engineering datasets to derive actionable insights.
- Evaluate model performance and drive continuous improvements.
Deep Learning & Computer Vision
- Develop deep learning models for:
- Defect classification
- Pattern recognition
- Image segmentation
- Object detection
- Feature extraction
- Build and optimize models using:
- PyTorch
- TensorFlow
- ONNX
- Work with image-processing pipelines and semiconductor inspection datasets.
Agentic AI & LLM Applications
- Develop AI assistants and workflow automation solutions using modern agent frameworks.
- Build Retrieval-Augmented Generation (RAG) pipelines.
- Integrate LLMs with enterprise data sources and engineering workflows.
- Develop tool-using AI agents capable of planning, reasoning, and workflow execution.
- Contribute to multi-agent systems for engineering productivity and analytics.
Software Engineering
- Design and implement production-quality software in:
- C++
- Python
- Convert business and system requirements into scalable AI solutions.
- Develop reusable software libraries, APIs, and services.
- Participate in code reviews and software design reviews.
- Optimize performance, scalability, and reliability of AI services.
Collaboration & Product Development
- Work closely with:
- Software Engineers
- Algorithm Engineers
- Product Managers
- Applications Teams
- Contribute to solution design discussions.
- Participate in feasibility studies and technical investigations.
- Support deployment, validation, and customer adoption activities.
Required Qualifications
Education
- Bachelor's, Master's, or PhD in:
- Computer Science
- Artificial Intelligence
- Machine Learning
- Statistics
- Mathematics
- Computer Engineering
- Related discipline
Experience
Typically:
- BS + 5 years experience
- OR MS + 3 years experience
- OR PhD with relevant experience
Consistent with the experience expectations for the P3 AI Engineering level.
Required Technical Skills
Programming
Strong proficiency in:
- Python
- Modern C++ (C++14/17/20)
Experience with:
- Data structures
- Algorithms
- Object-oriented design
- Multithreaded programming
Machine Learning
Experience developing and deploying:
- Random Forests
- XGBoost
- Gradient Boosting
- Isolation Forest
- Clustering Algorithms
- Predictive Models
Deep Learning
Hands-on experience with:
- PyTorch
- TensorFlow
- Deep Neural Networks
- CNNs
- Transformers
- Vision Models
Statistical Analytics
Strong understanding of:
- Probability & Statistics
- Experimental Design
- Statistical Inference
- Feature Engineering
- Data Validation
- Model Evaluation
Agentic AI
Exposure to one or more:
- LangGraph
- LangChain
- AutoGen
- CrewAI
- Semantic Kernel
- OpenAI Agents SDK
- MCP (Model Context Protocol)
Skills include:
- Tool Calling
- Workflow Orchestration
- RAG Systems
- Knowledge Retrieval
- AI Automation
Preferred Qualifications
- Semiconductor manufacturing experience.
- Yield analytics or defect analytics experience.
- Experience with:
- Vector databases
- Knowledge graphs
- Ray
- Spark
- Kubernetes
- Docker
- Experience building enterprise AI solutions.
What Success Looks Like
Within this role, you will:
- Independently deliver AI and machine-learning features.
- Design and deploy production-ready statistical and deep learning models.
- Build agentic AI capabilities that improve engineering productivity.
- Contribute to image-processing and advanced analytics solutions.
- Influence architecture and technical design decisions.
- Mentor junior engineers and contribute to engineering best practices.
Minimum Qualifications
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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