Principal Engineer in Automation, Machine Learning & AI

Job Description

We are looking for a Principal Engineer in Automation, Machine Learning (ML) & AI to lead the automation and AI-driven transformation of our wafer test (probe), final test, visual inspection, and packing operations. This role will be responsible for developing, integrating, and optimizing automation systems, leveraging ML and AI to improve cost, quality control, efficiency, and predictive analytics. The ideal candidate will also train and mentor our engineering team to build in-house expertise in automation, ML, and AI applications.

Key Responsibilities

• Automation & smart manufacturing implementation
• Design and implement automation solutions for wafer test, final test, visual inspection, and packing processes.
• Develop and integrate ATE, probe station automation, and handler robotics to enhance efficiency.
• Implement PLC, robotics, and IoT-based automation to minimize manual intervention.
• Optimize automated visual inspection with AI-based defect detection and marking verification.
• Machine Learning (ML) & AI integration
• Develop and deploy AI-driven machine vision for defect detection, OCR accuracy, and wafer/package quality inspection.
• Use ML algorithms for predictive maintenance to improve OEE of probe stations, testers, and handlers.
• Optimize test parameters dynamically with ML-based adaptive testing to reduce test time and improve yield.
• Apply AI to analyze test data, detect failure patterns, and recommend corrective actions.
• Data-driven process optimization & cost reduction
• Implement ML-based predictive analytics to improve yield, OEE, and defect classification.
• Reduce human reliance in visual inspection by enhancing AI-based self-learning models.
• Work with internal teams to reduce vendor dependency by developing in-house automation & AI solutions.
• Knowledge transfer & training
• Conduct hands-on training sessions to upskill engineers in automation, ML, and AI applications.
• Provide technical mentorship on AI-based test optimization and automation programming.
• Establish best practices for machine learning model deployment and continuous improvement.
  
  

Qualifications & Requirements

Education & Experience:

• Bachelor’s or Master’s degree in Electrical Engineering, Automation, Computer Science, AI, or a related field.
• 8+ years of experience in semiconductor automation, ML/AI development, or smart manufacturing.
  
  

Technical Skills

• Automation & Robotics: expertise in PLC programming, robotics, and IoT-based automation.
• Wafer Test & Final Test Optimization: Experience with ATE systems, handlers, probe stations, and scanners automation.
• Machine Learning & AI: Proficiency in Python, TensorFlow, PyTorch, MATLAB, and AI model deployment for predictive analytics.
• Machine Vision & Defect Detection: Experience in OCR, AI-based defect classification, and automated visual inspection.
• Data Analytics & Predictive Maintenance: Knowledge of big data analysis, ML-driven failure prediction, and OEE optimization.
  
  

Soft Skills

• Strong problem-solving and analytical skills for automation and AI-driven improvements.
• Excellent communication and training abilities to mentor engineers.
• Ability to work independently and drive automation/AI initiatives.
  
  

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