Design, develop, train, and deploy AI/ML models for manufacturing use cases.

Build end-to-end solutions from data acquisition and preprocessing to deployment and monitoring.

Work with machine, sensor, PLC, process, quality, and production data.

Develop solutions for use cases such as predictive maintenance, anomaly detection, quality prediction, process optimization, forecasting, and root-cause analysis.

Integrate AI solutions with machines, databases, APIs, MES/SCADA, and industrial IoT systems.

Deploy and operate models in cloud, on-premise, or edge environments.

Apply MLOps practices for model versioning, deployment, monitoring, and retraining.

Work directly with shopfloor and engineering teams to understand production processes and translate operational challenges into AI solutions

Required Qualifications


Degree in Computer Science, AI, Data Science, Engineering, Automation, Mechatronics, or a related field.

Strong hands-on experience in AI/ML development and production deployment.

Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, scikit-learn, Pandas, or similar.

Experience with time-series data, predictive modeling, anomaly detection, and data pipelines.

Experience with SQL, APIs, Docker, Git, CI/CD, and MLOps.

Good understanding of manufacturing environments and industrial/shopfloor data.

Ability to collaborate effectively with production, automation, process, quality, and maintenance engineers.

Preferred Experience

Experience with Industrial AI / AIoT, PLC data, OPC UA, MQTT, MES/SCADA, industrial IoT, edge computing, predictive maintenance, process optimization and cloud AI platforms is highly valuable