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# Senior Engineer Machine Learning / AI | Insurance Industry | Germany

- **Company:** Prometeo Talent
- **Location:** München, Germany (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon S3, Cloud Computing, Code Review, Continuous Integration, Machine Learning, Data Processing, Generative AI, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations, Docker
- **Published:** November 10, 2026
- **Apply:** https://www.adzuna.de/details/5959694976

## About the Role

* Master's degree or higher (a PhD is a plus) in Data Science, Machine Learning, Mathematics, Physics, Computer Science, or a related field.

 * Several years of hands-on experience as a Machine Learning Engineer, AI Engineer, or in a comparable technical role.

 * Strong knowledge of machine learning engineering and operating AI solutions in production.

 * Experience with Docker, Kubernetes, Infrastructure as Code, CI/CD pipelines, MLflow, and Airflow.

 * Hands-on experience with AWS services such as S3, Step Functions, Lambda, SageMaker, and Bedrock.

 * Strong communication skills and a high sense of ownership over projects and outcomes.

## Description

We are looking for a Senior Machine Learning / AI Engineer to build the technical foundations for scalable AI applications and agent systems. You will work closely with Data Scientists, MLOps specialists, business stakeholders, and IT experts, owning the full lifecycle of production AI solutions, from data processing to deployment and operations. Your main responsibilities will be:

 * Design and implement cloud-based AI solutions across machine learning, generative AI, and agent systems.

 * Deploy and operate scalable ML and GenAI workloads in production together with the MLOps teams.

 * Select and introduce modern architectures and tools for ML workflows, helping shape the organization's Data Science and AI technology stack.

 * Define and implement technical standards and best practices for Machine Learning Engineers and Data Scientists.

 * Mentor colleagues through code reviews and coaching, especially in cloud technologies and ML engineering.

 * Take end-to-end ownership of AI solutions, from data processing through production operations, collaborating with Data Science, business, and IT teams.