AI Manufacturing Engineer

About the role

Itron is innovating new ways for utilities and cities to manage energy and water. We create a more resourceful world to protect essential resources for today and tomorrow. Join us. The AI Manufacturing Engineer designs, develops, deploys, and supports AI-enabled solutions that enhance manufacturing processes, test systems, product quality, and factory operations. This role combines expertise in industrial engineering, data science, machine learning, software development, and manufacturing systems to solve complex operational challenges in a technology-driven Utilities & Energy environment. The ideal candidate is passionate about applying artificial intelligence technologies to real-world manufacturing environments and can translate business needs into practical, scalable solutions that improve operational performance, customer outcomes, and business value. The successful candidate demonstrates a customer-centric mindset, accountability for results, and the ability to collaborate effectively across cross-functional teams.

Responsibilities

• 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.

Requirements

• 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,