Model Development & Deployment

• Architect, train, and operationalize machine learning models for predictive maintenance, anomaly detection, and manufacturing process optimization.
• Build Generative AI applications such as automated reporting systems, intelligent virtual assistants, and production scenario simulation tools.
• Convert experimental AI/ML algorithms into scalable, production-grade solutions by applying MLOps best practices.

Data Engineering & Integration

• Design and maintain reliable data pipelines to ingest, cleanse, and transform sensor, MES, and IoT data for model training and real-time inference.
• Integrate AI solutions with factory automation systems and Manufacturing Execution Systems (MES) to enable data-driven operational decisions.

Predictive Analytics & Quality Control

• Leverage machine learning and AI techniques to predict equipment breakdowns, optimize manufacturing ...