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:

1.

Software

Engineers

2.

Algorithm

Engineers

3.

Product

Managers

4.

Applications

Teams

- Contribute to solution design discussions.
- Participate in feasibility studies and technical investigations.
- Support deployment, validation, and customer adoption activities.

Required Qualifications:

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:

- Robust 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:

1.

Random

Forests

- XGBoost

3.

Gradient

Boosting

4.

Isolation

Forest

5.

Clustering

Algorithms

6.

Predictive

Models

Deep Learning:

- Hands-on experience with:
- PyTorch
- TensorFlow

3.

Deep Neural

Networks

- CNNs
- Transformers

6.

Vision

Models

Statistical Analytics:

- Strong understanding of:
- Probability &
- Statistics

2.

Experimental

Design

3.

Statistical

Inference

4.

Feature

Engineering

- Data Validation

6.

Model

Evaluation

Agentic AI:

- Exposure to one or more:
- LangGraph
- LangChain
- AutoGen
- CrewAI

5.

Semantic

Kernel

- OpenAI Agents SDK
- MCP (Model Context Protocol)
- Skills include:
- Tool Calling

2.

Workflow

Orchestration

- RAG Systems

4.

Knowledge

Retrieval

- AI Automation

What Success Looks Like:

- 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.

📌 KLA - AI Engineer - LangChain/Deep Learning (India)
🏢 KLA
📍 India