Your tasks:
► You will design, develop, and validate data-driven models and AI solutions to support Engineering and Manufacturing use cases within the Semiconductor and ECU domain;
► You will explore, analyze, and transform complex engineering and manufacturing data to generate actionable insights and enable predictive and prescriptive solutions;
► You will develop, train, evaluate, and deploy machine learning and AI models (e.g. forecasting, anomaly detection, optimization, computer vision) on the engineering and manufacturing data platforms;
► You will work with diverse data types, data sources, and existing building blocks (e.g. APIs, microservices, feature stores) in close collaboration with data engineers and domain experts;
► You will design and operate end-to-end ML pipelines, including data preparation, model training, validation, deployment, monitoring, and retraining;
► You will define and implement strategies for model quality, explainability, robustness, and lifecycle management, including monitoring of data and model drift;
► In addition, you will contribute to the industrialization of AI solutions, including automated integration, orchestration, and scalable deployment of models into manufacturing and engineering environments.
Join us as a key enabler for AI-driven digitalization in Engineering and Manufacturing at ME.