Germany
Siemens
Adesso SE
Senior Machine Learning Engineer / Data Scientist
Germany
Cologne, North Rhine-Westphalia, Germany · Dortmund, North Rhine-Westphalia, Germany · Dusseldorf, North Rhine-Westphalia, Germany · Essen, North Rhine-Westphalia, Germany · Münster, North Rhine-Westphalia, Germany · Kiel, Schleswig-Holstein, Germany · Neumünster, Schleswig-Holstein, Germany · Berlin, Germany · Hamburg, Germany
PythonDocker
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YOUR ROLE *
- Develop AI Services: You conceptualize, develop, and implement new Machine-Learning models that intelligently enhance our software – for example, for automated evaluation of medical data, text classification, or decision support in invoice processing. *
- Model Integration and MLOps: You seamlessly integrate ML models into our product architecture, automate training and deployment pipelines, and ensure the traceability and maintainability of production models. *
- Quality and Performance: You are responsible for the continuous monitoring and improvement of model quality, conduct retraining, and establish metrics for model evaluation and optimization. *
- Data Analysis and Feature Engineering: You analyze medical and billing-related data, derive relevant features, and ensure data quality, consistency, and security. *
- Interdisciplinary Collaboration: You work closely with subject matter experts, product management, and software development to embed AI-based functions into our auditing software and create practical added value for health insurance companies and service providers.
YOUR PROFILE *
- Education/Training: Successfully completed studies in Computer Science, Data Science, Medical Informatics, or a comparable degree program with a technical focus. *
- Experience: Several years of professional experience in the development, implementation, and support of production Machine-Learning models – ideally in a regulated or data-driven environment such as healthcare, insurance, or the public sector. *
- Technical Skills (ML & Data Science): Profound knowledge of Python and common ML frameworks (scikit-learn, TensorFlow, PyTorch) as well as experience with model evaluation and feature engineering. *
- Technical Skills (MLOps & Architecture): Experience with MLOps tools and processes (e.g., MLflow, Kubeflow), containerization (Docker), and CI/CD. Knowledge of data pipelines is required. *
- Soft Skills: Analytical thinking, strong problem-solving skills, affinity for medical and regulatory issues, and the ability to communicate complex AI concepts clearly and practically. *
- Innovations: Interest in new technologies and innovations (e.g., use of LLMs). *
- Language Skills: Very good German language skills (C1 level).
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