AI Application Engineer

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 (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 Qualifications

• 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