Design and develop data processing frameworks and analytical models for industrial web surface inspection systems to improve image acquisition accuracy, preprocessing methodologies, and overall workflow efficiency. Develop, test, and optimize machine learning and computer vision models, including deep learning-based classification and detection algorithms, for automated defect recognition and quality inspection applications. Implement and maintain database system pipelines using Python and SQL to retrieve, organize, and ensure accessibility of client large-scale image data for routine analysis of performance Conduct quantitative analyses on imaging accuracy, defect detection performance, inspection efficiency, and system reliability to support product enhancement and research initiatives. Collaborate with field application engineer teams to evaluate experimental results, troubleshoot data issues, and optimize machine vision inspection systems for client-specific applications. Collaborate with international analytics teams to test, validate, and analyze new system functionalities by evaluating performance metrics, interpreting operational data, and ensuring consistent system accuracy and efficiency across global deployments. Integrate operational and analytical datasets with ERP system Kingdee to ensure data consistency, improve reporting accuracy, and support business analytics initiatives Minimum Requirements: Masters Degree in Data Science, Applied Urban Science and Informatics, Statistics, Computer Science, or a related field. Proficient with Microsoft Office, Python and SQL. Strong skills in quantitative methodologies, applied statistics analysis, and model building. Excellent communication, interpersonal, and problem-solving skills. How to Apply: Interested Candidates may submit their cover letter and resume to Wintriss Engineering Corp 9770 Carroll Centre RD, Ste D, San Diego, CA 92126
