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Design and implement scalable AI architectures in hybrid and cloud environments (Azure, AWS, GCP)
Integrate production systems (SCADA, MES, DCS) and IIoT components using OPC UA, MQTT, and Modbus
Develop secure, high-performance data pipelines from OT/edge environments to data lakes and cloud platforms
Support real-time applications for monitoring, anomaly detection, early warning, and forecasting
Define interfaces (REST/gRPC) and workflows for machine learning model deployment and orchestration (e.g., MLflow, Kubeflow)
Collaborate with ML Engineers, Data Scientists, and DevOps teams to deliver full end-to-end AI solutions
Use SQL for data modeling, transformation, and integration
Contribute to data governance, lineage, and compliance (e.g., GDPR, ISO/IEC 27001) Several years of experience designing data-driv...
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