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Advanced Manufacturing Technology (AMT) AI Automation Engineer
Reports to: Engineering Manager
Direct Reports: None
Main Function:
This role is responsible for developing and deploying AI-driven solutions to enhance automation, test engineering, and quality control. The engineer focuses on machine learning, computer vision, and analytics to optimize manufacturing performance, defect detection, traceability, and predictive support. Duties and Responsibilities Design, develop, train, and deploy machine learning models for applications such as defect detection, data prediction, performance classification, and production anomaly identification. Implement image recognition and computer vision algorithms to support automated optical inspection (AOI), test result interpretation, and component/process verification on production lines. Collaborate with Engineering departments to identify use cases where AI can optimize testing logic, reduce test cycle time, and enhance decision-making processes. Collaborate with IT to integrate AI models into the existing Digital Factory Management System (DFMS) to enable real-time analytics, feedback loops, and intelligent test control. Build and maintain data pipelines for training and validating AI models using structured and unstructured data from automation machines, test equipment, servers, sensors, and vision systems. Support failure analysis and root cause investigations using AI to uncover hidden patterns in large datasets and enable predictive alerts for failure trends. Drive continuous improvement initiatives through AI-powered solutions that increase test process reliability, reduce false failures, and support traceability and compliance. Collaborate with IT (Infrastructure), Automation, and Engineering to ensure hardware compatibility, model deployment at the edge or server level, and secure data handling. Contribute to digital transformation initiatives by integrating AI with existing systems and replacing manual processes with smart, automated, and connected systems. Support the development of digital twins for automated machines and test processes, enabling predictive solutions for early failure detection and process optimization. Maintain documentation of AI models, workflows, and data interfaces to ensure version control, reproducibility, and alignment with security and compliance standards. Perform other tasks as assigned.
Education Required
Bachelor's degree in Computer Science, Artificial Intelligence, or Data Science. Masters degree in AI, Machine Learning, or Computer Vision.
Experience Required
Minimum 3 years of experience developing and deploying AI/ML models in production environments, preferably in manufacturing for electronic components. Experience working with test or inspection data (e.g., image, log, or signal data) in structured manufacturing environments. Experience integrating AI with automated test equipment or vision systems. Exposure to MES platforms and digital manufacturing systems.
Foxconn provides equal employment opportunity (EEO) to all employees and job applicants, regardless of age, race, gender, religion, or genetics. In addition to federal law requirements, Foxconn complies with applicable state and local laws governing nondiscrimination in employment. This policy applies to all employment terms and conditions, including recruitment, hiring, promotion, termination, and training. #J-18808-Ljbffr
This role is responsible for developing and deploying AI-driven solutions to enhance automation, test engineering, and quality control. The engineer focuses on machine learning, computer vision, and analytics to optimize manufacturing performance, defect detection, traceability, and predictive support. Duties and Responsibilities Design, develop, train, and deploy machine learning models for applications such as defect detection, data prediction, performance classification, and production anomaly identification. Implement image recognition and computer vision algorithms to support automated optical inspection (AOI), test result interpretation, and component/process verification on production lines. Collaborate with Engineering departments to identify use cases where AI can optimize testing logic, reduce test cycle time, and enhance decision-making processes. Collaborate with IT to integrate AI models into the existing Digital Factory Management System (DFMS) to enable real-time analytics, feedback loops, and intelligent test control. Build and maintain data pipelines for training and validating AI models using structured and unstructured data from automation machines, test equipment, servers, sensors, and vision systems. Support failure analysis and root cause investigations using AI to uncover hidden patterns in large datasets and enable predictive alerts for failure trends. Drive continuous improvement initiatives through AI-powered solutions that increase test process reliability, reduce false failures, and support traceability and compliance. Collaborate with IT (Infrastructure), Automation, and Engineering to ensure hardware compatibility, model deployment at the edge or server level, and secure data handling. Contribute to digital transformation initiatives by integrating AI with existing systems and replacing manual processes with smart, automated, and connected systems. Support the development of digital twins for automated machines and test processes, enabling predictive solutions for early failure detection and process optimization. Maintain documentation of AI models, workflows, and data interfaces to ensure version control, reproducibility, and alignment with security and compliance standards. Perform other tasks as assigned.
Education Required
Bachelor's degree in Computer Science, Artificial Intelligence, or Data Science. Masters degree in AI, Machine Learning, or Computer Vision.
Experience Required
Minimum 3 years of experience developing and deploying AI/ML models in production environments, preferably in manufacturing for electronic components. Experience working with test or inspection data (e.g., image, log, or signal data) in structured manufacturing environments. Experience integrating AI with automated test equipment or vision systems. Exposure to MES platforms and digital manufacturing systems.
Foxconn provides equal employment opportunity (EEO) to all employees and job applicants, regardless of age, race, gender, religion, or genetics. In addition to federal law requirements, Foxconn complies with applicable state and local laws governing nondiscrimination in employment. This policy applies to all employment terms and conditions, including recruitment, hiring, promotion, termination, and training. #J-18808-Ljbffr