Inspection Software Engineer

KEY RESPONSIBILITIES

• Design, develop, and validate deep learning models (CNN-based or equivalent) for automated defect classification within the online inspection system.
• Implement Auto-Judgment (AJ) logic to generate automated dispositions on production sheets based on predefined quality criteria and inspection outputs.
• Lead system integration between machine learning components and production inspection hardware and software platforms.
• Partner with manufacturing, quality, and engineering teams to define defect categories, classification thresholds, and acceptance criteria.
• Monitor deployed model performance, analyze classification accuracy, and retrain or optimize models as production data evolves.
• Document technical specifications, model validation results, and system integration procedures.

REQUIRED QUALIFICATIONS

• Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related field.
• 3+ years of software development experience with a focus on machine learning or computer vision applications.
• Proficiency in at least one backend programming language; Experienced in PyTorch;
• Proficiency in git, docker and sql
• Experienced in using common middleware
• Hands-on experience developing and deploying image classification or defect detection models in an industrial or production environment.
• Experience integrating machine learning components with hardware or software inspection systems.
• Fluency in Mandarin Chinese (written and spoken).
• Functional English proficiency sufficient for cross-regional technical communication.

DESIRED / PREFERRED QUALIFICATIONS

• Hands-on experience with CNN-based defect classification in a manufacturing quality context.
• Proficiency in CSharp(C#, .net); Vue3 or any front end framework; Linux;
• Familiarity with automated optical inspection (AOI) systems or equivalent online inspection platforms.
• Experience with image processing libraries such as OpenCV.
• Experience optimizing models for edge or embedded deployment (e.g., ONNX, TensorRT).
• Knowledge of quality control standards and manufacturing disposition processes.

SKILLS / COMPETENCIES

• Applies deep learning and computer vision techniques to solve real-world defect classification problems in a manufacturing environment.
• Integrates machine learning models with industrial inspection systems with minimal supervision.
• Translates quality criteria and manufacturing requirements into model training parameters and judgment logic.
• Communicates technical findings clearly to cross-functional stakeholders in both Mandarin and English.