Semiconductor AI Manufacturing Analytics Engineer

AI, Machine Learning & Smart Manufacturing Analytics

Location: Bengaluru / Ahmedabad / Dholera / Sanand, India
Work Mode: Onsite / Hybrid
Experience: 5- 12 Years
Industry: Semiconductor Manufacturing | Foundry | OSAT | AI | Smart Factory

Role Overview

We are seeking an experienced Semiconductor AI Manufacturing Analytics Engineer to develop and deploy Artificial Intelligence (AI), Machine Learning (ML), and Advanced Analytics solutions that improve semiconductor manufacturing performance. The role focuses on applying AI to yield enhancement, process optimization, predictive maintenance, defect detection, statistical process control (SPC), fault detection and classification (FDC), advanced process control (APC), and smart factory initiatives.
The successful candidate will work closely with Manufacturing, Process Integration, Equipment Engineering, Yield Engineering, Quality, Data Engineering, and Digital Transformation teams to build AI-powered manufacturing solutions that improve productivity, equipment utilization, product quality, and manufacturing efficiency.
Key Responsibilities
Develop AI and Machine Learning models for semiconductor manufacturing and process optimization.
Build predictive analytics solutions for yield improvement, defect prediction, equipment health monitoring, and process control.
Analyze large-scale manufacturing datasets from wafer fabrication, assembly, packaging, and semiconductor test operations.
Design AI-driven solutions for Statistical Process Control (SPC), Fault Detection & Classification (FDC), and Advanced Process Control (APC).
Develop predictive maintenance models for semiconductor manufacturing equipment to reduce downtime and improve Overall Equipment Effectiveness (OEE).
Build AI-based root cause analysis frameworks using manufacturing, metrology, and equipment data.
Collaborate with Process, Equipment, Yield, Manufacturing, Quality, and Automation teams to identify digital transformation opportunities.
Develop dashboards, KPIs, and visualization tools for engineering and factory leadership.
Integrate AI applications with MES, Manufacturing Data Systems, Equipment Automation, and Factory Information Systems.
Deploy AI models into production environments while monitoring performance and continuous improvement.
Support Digital Twin initiatives for semiconductor manufacturing.
Document AI methodologies, validation reports, and technical recommendations.
Required Qualifications
Bachelor's or Master's degree in Electronics Engineering, Computer Science, Data Science, Artificial Intelligence, Industrial Engineering, Mechanical Engineering, or related discipline.
5 12 years of experience in Semiconductor Manufacturing, Manufacturing Analytics, AI/ML Engineering, or Industrial Data Analytics.
Strong understanding of semiconductor manufacturing processes and factory operations.
Experience applying AI or Machine Learning to industrial or manufacturing environments.
Technical Skills Semiconductor Manufacturing
Wafer Fabrication
Semiconductor Assembly
Advanced Packaging
Semiconductor Test
Manufacturing Operations
Yield Engineering
Process Integration
Equipment Engineering
Smart Factory
Manufacturing Analytics
Statistical Process Control (SPC)
Fault Detection & Classification (FDC)
Advanced Process Control (APC)
Overall Equipment Effectiveness (OEE)
Root Cause Analysis
Yield Analytics
Process Monitoring
Equipment Analytics
Manufacturing KPIs
Artificial Intelligence & Machine Learning
Machine Learning
Deep Learning
Predictive Analytics
Computer Vision
Anomaly Detection
Time Series Forecasting
Reinforcement Learning (Preferred)
Generative AI
Large Language Models (LLMs)
AI Agents
Programming & Data Engineering
Python
SQL
PySpark
Pandas
NumPy
Scikit-learn
TensorFlow
PyTorch
Databricks
Apache Spark
Cloud & Infrastructure
Microsoft Azure
AWS
Google Cloud Platform
Snowflake
Docker
Kubernetes
MLflow
Visualization & BI
Power BI
Tableau
Grafana
Kibana
Excel


#LI-SD1
Show more Show less