Semiconductor AI Manufacturing Analytics Engineer

Best NanoTech; Bengaluru; Hybrid; INR 1,500,000 - 2,100,000; Full time

Job summary

Best NanoTech in Bengaluru seeks an experienced Semiconductor AI Manufacturing Analytics Engineer to develop and deploy AI/ML solutions that boost yield, optimize processes, and enable smart factory initiatives.

You will work with Manufacturing, Process Integration, Equipment Engineering, Yield, Quality, Data Engineering, and Digital Transformation teams to deliver AI-powered manufacturing insights that improve productivity, equipment utilization, and product quality.

Qualifications

• Bachelor's or Master's degree in Electronics Engineering, Computer Science, Data Science, AI, Industrial Engineering, Mechanical Engineering or related field.
• 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 ML to industrial or manufacturing environments.

Responsibilities

• Develop AI/ML models for semiconductor manufacturing and process optimization.
• Build predictive analytics 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 SPC, FDC, and APC.
• Develop predictive maintenance models to reduce downtime and improve OEE.
• Build AI-based root cause analysis using manufacturing, metrology, and equipment data.
• Collaborate with Process, Equipment, Yield, Manufacturing, Quality, and Automation teams on digital transformation.
• Develop dashboards, KPIs, and visualization tools for engineering and factory leadership.
• Integrate AI applications with MES and Factory Information Systems.
• Deploy AI models into production with monitoring and continuous improvement.
• Support Digital Twin initiatives for semiconductor manufacturing.
• Document AI methodologies, validation reports, and technical recommendations.

Skills

AI/ML engineering

Manufacturing analytics

SPC

APC

OEE

Yield analytics

Data engineering

Defect detection

Education

Electronics Eng

Computer Science

Data Science

Job description

AI, Machine Learning & Smart Manufacturing Analytics

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
• Advanced Packaging
• Semiconductor Test
• Manufacturing Operations
• Process Integration
• Smart Factory

Manufacturing Analytics

• Statistical Process Control (SPC)
• Advanced Process Control (APC)
• Overall Equipment Effectiveness (OEE)
• Yield Analytics
• Process Monitoring
• Equipment Analytics
• Manufacturing KPIs

Artificial Intelligence & Machine Learning