AI Manufacturing Engineer

Itron, Inc.

. Design, develop, deploy, and support AI-enabled solutions for manufacturing processes, test systems, product quality, and factory operations.

Posted 9/29/2026full-timeUnited StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI-enabled solutions for manufacturing processes, including machine learning model development, predictive analytics, and computer vision applications. Proficient in collaborating with cross-functional teams to drive operational improvements and ensure compliance with industry standards.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProgrammingMLOps and Model DeploymentData Analysis and Predictive ModelingManufacturing Process Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPredictive AnalyticsComputer VisionData ProcessingSQL DatabasesTensorFlowPyTorchScikit-LearnDashboard DevelopmentAI Governance

Soft Skills

Problem-SolvingAnalytical ThinkingEffective CommunicationCollaborationProject Management

Tools & Technologies

MESERPPLMData Visualization ToolsDigital Twins

Industry Keywords

Industry 4.0Manufacturing EngineeringQuality SystemsOperational EnvironmentsContinuous Improvement

Tech Stack

Tools & technologies

Cyber SecurityERPPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Design, develop, deploy, and support AI-enabled solutions for manufacturing processes, test systems, product quality, and factory operations.
Develop, train, validate, and deploy machine learning models for manufacturing applications.
Build predictive analytics solutions to 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 and prioritize AI use cases.
Support Industry 4.0 initiatives through AI-enabled manufacturing solutions.
Integrate AI applications with MES, ERP, PLM, manufacturing databases, test systems, and production equipment.
Create dashboards, monitoring tools, and decision-support systems.
Implement digital twins and process simulation capabilities.
Develop scalable data pipelines for structured and unstructured manufacturing data.
Ensure model accuracy, reproducibility, data integrity, cybersecurity requirements, and regulatory compliance.
Establish and maintain AI governance, model monitoring, lifecycle management, and responsible AI deployment practices.
Partner with Manufacturing Engineering to improve production yields, cycle times, OEE, capacity utilization, and process stability.
Support NPI activities through manufacturing analytics and process optimization.
Collaborate with Test Engineering to improve automated test coverage, diagnostic capability, and test efficiency.
Participate in continuous improvement initiatives using AI-driven insights.
Work cross-functionally with Operations, Quality, Product Development, Supply Chain, IT, and other stakeholders.
Communicate technical findings, recommendations, and project outcomes to technical and non-technical audiences.
Provide guidance, training, and mentorship on AI technologies, advanced analytics, and data-driven decision-making.
Stay current on emerging AI technologies, manufacturing innovations, industry trends, and best practices.
Demonstrate accountability for project execution, deliverables, and measurable business impact.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Competitive benefit package
Financial programs
Social programs
Health and wellbeing programs
Paid vacation
401k matching
Employee stock purchase program
Hybrid work schedule