AI Manufacturing Engineer

• Develop, train, validate, and deploy machine learning models for manufacturing applications.
• Build predictive analytics solutions that improve product quality, throughput, equipment reliability, process optimization, and customer outcomes.
• Design AI-based systems for anomaly detection, defect classification, root-cause analysis, and predictive maintenance.
• Develop computer vision solutions for automated inspection, quality assurance, and manufacturing process verification.
• Collaborate with manufacturing, quality, operations, and test engineering subject matter experts to identify high-value AI use cases and prioritize implementation opportunities.
• Support Industry 4.0 initiatives through the deployment of AI-enabled manufacturing solutions that drive operational excellence and innovation.
• Integrate AI applications with Manufacturing Execution Systems (MES), Enterprise Resource Planning (ERP) platforms, Product Lifecycle Management (PLM) systems, manufacturing databases, test systems, and production equipment.
• Create dashboards, monitoring tools, and decision-support systems that transform manufacturing data into actionable insights.
• Implement digital twins and process simulation capabilities to improve manufacturing efficiency and decision-making.
• Develop scalable data pipelines for structured and unstructured manufacturing data from production, quality, and operational systems.
• Ensure model accuracy, reproducibility, data integrity, cybersecurity requirements, and regulatory compliance.
• Establish and maintain best practices for AI governance, model monitoring, lifecycle management, and responsible AI deployment.
• Partner with Manufacturing Engineering teams to improve production yields, cycle times, Overall Equipment Effectiveness (OEE), capacity utilization, and process stability.
• Support New Product Introduction (NPI) activities through data-driven manufacturing analytics and process optimization.
• Collaborate with Test Engineering teams to improve automated test coverage, diagnostic capability, and test efficiency.
• Participate in continuous improvement initiatives using AI-driven insights and data-informed decision making.
• Work cross-functionally with Operations, Quality, Product Development, Supply Chain, Information Technology, and other stakeholders to deliver business results.
• Communicate technical findings, recommendations, and project outcomes effectively to both technical and non-technical audiences.
• Provide guidance, training, and mentorship on AI technologies, advanced analytics, and data-driven decision-making practices.
• Stay current on emerging AI technologies, manufacturing innovations, industry trends, and best practices.
• Demonstrate accountability for project execution, deliverables, and measurable business impact while contributing to a culture of agility, collaboration, authenticity, and innovation.

• Bachelor’s degree in Computer Science, Electrical Engineering, Industrial Engineering, Data Science, Manufacturing Engineering, or a related technical field.
• Experience developing solutions using Python or similar programming languages.
• Experience with MLOps, model deployment, monitoring, and lifecycle management.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-Learn, or equivalent technologies.
• Experience with data analysis, statistics, predictive modeling, and advanced analytics techniques.
• Experience working with SQL databases, data processing tools, and large-scale datasets.
• Understanding of manufacturing processes, industrial automation, quality systems, operational environments, or related production systems.
• Experience in manufacturing engineering, industrial engineering, test engineering, quality engineering, operations engineering, or related disciplines.
• Experience implementing AI agents and intelligent automation solutions for manufacturing and quality process improvements.
• Experience developing dashboards, reporting tools, and data visualization solutions.
• Strong problem-solving, analytical thinking, and root-cause investigation skills.
• Ability to communicate complex technical concepts clearly and effectively to diverse audiences.
• Ability to work collaboratively across multiple functions, teams, and geographic locations.
• Strong project management, execution, and organizational skills.
• Demonstrated ability to deliver customer-focused solutions that drive operational improvements and business results.
• Commitment to continuous learning, innovation, accountability, and inclusive collaboration.
• Experience with computer vision, industrial image processing, and automated inspection technologies.
• Experience with cloud platforms such as Microsoft Azure and cloud-based AI services.
• Knowledge of Industrial Internet of Things (IIoT), MES, SCADA, PLCs, industrial control systems, and manufacturing data platforms.
• Experience deploying AI and machine learning solutions in production manufacturing environments.
• Familiarity with Statistical Process Control (SPC), Six Sigma, Lean Manufacturing, Kaizen, or continuous improvement methodologies.
• Knowledge of electronics manufacturing, utility products, smart metering technologies, test systems, industrial equipment, or energy-focused manufacturing operations.
• Experience working with digital twin technologies, simulation tools, or advanced manufacturing analytics platforms.
• Familiarity with data governance, responsible AI practices, cybersecurity principles, and regulatory compliance requirements.
• Experience supporting smart factory, connected factory, or Industry 4.0 transformation initiatives.
• Advanced degree in a relevant engineering, computer science, data science, or analytics discipline.

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