AI Application Engineer
generacWaukesha (WI)
About the role
The AI Applications Engineer will design, develop, and deploy scalable AI/ML solutions that accelerate digital transformation across manufacturing operations. This role will focus on translating operational challenges into deployable AI solutions—integrating operations platforms to enable smarter decision-making, automation, and predictive insights. This position plays a critical role in building the "Digital Factory + AI" capability stack. This position could include up to 25% travel locally.
Major Responsibilities:
AI Solution Development & Deployment Design, build, test, and deploy machine learning and AI models, including productionizing solutions and maintaining model performance over time. Manufacturing (Operations) Use Case Delivery Develop and support AI solutions for shop floor applications such as predictive maintenance, quality inspection, yield optimization, and throughput improvement. Data Engineering & Platform Integration Develop data pipelines, integrate with enterprise systems, and ensure scalable, reusable AI and data architecture. Cross-Functional Collaboration & Business Translation Partner with Operations and IT teams to define use cases, translate business problems into AI solutions, and ensure adoption. Including build vs. buy analysis. Continuous Improvement, Governance & Documentation Monitor model performance, ensure data/model governance, document solutions, and drive reusability and standardization across sites/functions.
Minimum Job Requirements:
Education Bachelor's degree in computer science, engineering, data science, or related field Work Experience Experience working with structured and unstructured data Experience building and deploying AI based vision systems 5 years in manufacturing / OT environments, PLC, SCADA, MES exposure 2 years of experience in AI/ML development and deployment Knowledge / Skills / Abilities Python (Tensor Flow, PyTorch, Scikit-learn)Data engineering and ETL pipelines Model deployment (APIs, microservices, Docker, etc.)Understanding of industrial systems, manufacturing processes, or IoT data Strong problem-solving and systems thinking mindset Ability to bridge technical and business domains Execution-focused with a bias toward deployment (not just modeling)Ability to work across operations, engineering, and service functions Ability to demonstrate clear communication with both technical teams and leadership
Preferred Job Requirements:
Education Master's Degree Work Experience Experience in discrete manufacturing environments Experience working in digital factory or Industry 4.0 initiatives Familiarity with MES, PLM, and ERP integrations (SAP, Tulip, Windchill, etc.)Knowledge / Skills / Abilities Experience with Computer vision (OpenCV, vision models)Time-series analysis (sensor, telemetry data)Edge AI deployment
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