Full Job Description
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 (TensorFlow, 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