Industrial AI Engineer
Indexed description
The role focuses on site readiness, system integration, testing and operational handover. Initial project areas include AI vision inspection in Tennessee and digital twin applications for factory layout and material flow planning in Alabama.
Key Responsibilities
- Work with plant teams to define use cases, process constraints and measurable acceptance criteria, such as inspection accuracy, false rejects, missed defects, cycle time and material flow performance.
- Coordinate local delivery with implementation partners and headquarters. Track technical dependencies, resolve site issues and communicate progress, risks and decisions.
- Coordinate image and equipment data collection, labeling requirements and data quality checks. Work with engineering and automation teams on camera, lighting and equipment readiness.
- Work with SAP, MES and EWM application teams to define and test interfaces between AI solutions, manufacturing systems and equipment. Develop or troubleshoot integration scripts and data exchanges within the agreed scope.
- Prepare factory layout, cycle time and logistics inputs with industrial engineering teams. Support digital twin scenario testing and validate assumptions and results with process owners.
- Prepare and execute integration and user acceptance tests. Investigate failures, document results and support controlled deployment into production.
- Complete technical handover from implementation partners, including system documentation, support procedures, training and escalation paths. Provide local troubleshooting and coordinate specialist support.
- Monitor operational performance and recurring issues after launch. Coordinate model or configuration updates with solution owners and implementation partners.
- Work with Infrastructure & Operations on connectivity, access permissions, edge computing, monitoring and recovery arrangements. Follow plant safety, cybersecurity and change management procedures.
- Bachelor’s degree in computer science, electrical engineering, automation, industrial engineering or a related discipline, or equivalent relevant practical experience.
- At least 3 years of relevant experience in manufacturing systems, industrial automation, machine vision or industrial systems integration.
- Hands-on participation in at least one industrial project from requirements and testing through deployment or operational support.
- Understanding of manufacturing operations, including production cycle times, quality inspection, traceability or material flow.
- Ability to read, modify and troubleshoot Python or comparable scripts, use SQL to investigate data, and work with APIs or other system interfaces.
- Ability to troubleshoot across applications, data flows and equipment interfaces, using logs and structured problem-solving methods.
- Working understanding of industrial AI or machine vision concepts and the ability to evaluate solution performance against business requirements.
- Clear spoken and written English, with the ability to coordinate plant teams and remote technical partners and produce useful technical documentation.
- Automotive manufacturing, injection molding, assembly or new factory launch experience.
- Experience with machine vision tools or systems, such as Cognex, Keyence, HALCON or OpenCV, including image acquisition and lighting considerations.
- Exposure to NVIDIA Omniverse or other factory simulation and digital twin platforms.
- Familiarity with MES, SAP S/4HANA or EWM, and equipment connectivity through OPC UA, MQTT, PLCs or SCADA.
- Experience with Linux, containers, edge computing or maintaining AI applications in production.
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