Inspection Software Engineer

申请编号: 79462 这是一家立足于突破的公司。 加入我们。 康宁是全球领先的玻璃、陶瓷和材料科学创新引领者之一。从海洋深处到浩瀚宇宙，我们的技术不断突破可能性的边界。 我们是如何做到的？依靠我们的员工。在康宁，我们的员工独树一帜、突破常规——这不仅限于职业生涯的某一时刻，而是每一天，都在帮助推动公司及世界的进步。 在康宁，你所做的工作有数之不尽的机会对世界和人类产生积极的影响。你能帮助世界互联互通，驱动汽车的未来，让家庭娱乐更精彩，使救生药品安全送达。你能改变的远不止于此。 加入我们，一同突破。 康宁公司的显示科技事业部生产主要应用于LCD电视、笔记本电脑和平板显示器的有源矩阵液晶显示器（“LCD”）玻璃基板。 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. 康宁致力于提供平等就业机会，并根据适用的法律考虑合理便利申请。残障人士或有宗教信仰的人员可申请合理便利，以便参与应聘，工作或享受公司福利和权益。如需申请与残障或宗教相关的合理便利，请通过accommodations@corning.com联系我们。