> Markdown version of [/jobs/ext/3222470-machine-learning-application-developer](https://www.wearedevelopers.com/jobs/ext/3222470-machine-learning-application-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Application Developer

- **Company:** Eumetsat - European Organisation For The Exploitation Of Meteorological Satellites
- **Location:** Darmstadt, Germany
- **Salary:** €96,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Machine Learning, Cloud Platform System, Kubernetes, Free and Open-Source Software, Machine Learning Operations
- **Published:** September 16, 2026
- **Apply:** https://www.eurosciencejobs.com/job_display/296518/Machine_Learning_Application_Developer_EUMETSAT_European_Organisation_for_the_Exploitation_of_Meteorological_Satellites_Darmstadt_Germany

## About the Role

Master's or higher degree in a relevant computing or natural sciences subject., * Experience in ML model development and evaluation, preferably in weather and climate or Earth observation domain;

 * Experience with at least one of the relevant ML libraries (Scikit Learn, TensorFlow, Keras, PyTorch…);
 * Proven strong programming skills in at least Python and some experience in working with compiled languages and with modern collaborative software development practices, including Git-based development workflows, CI/CD pipelines, code review, and automated testing;
 * Experience in working with large datasets;
 * Experience in working in cloud environments;
 * Eagerness to learn and expand one's own knowledge, combined with ease in joining teams to solve problems and communicate resolutions;
 * Excellent communication skills, with a proven ability to work effectively as part of a team, strong problem-solving skills, and a positive, can-do attitude.

The below skills and experience are seen as an advantage:

 * Experience in working with Earth observation and weather and climate data;
 * Experience in using machine learning pipelines and frameworks (MLFlow, Kubeflow, etc.);
 * Contributions to the open-source software ecosystems., Candidates must be able to work effectively in English.

## Description

* Support EUMETSAT internal and external users by creating data pipelines and curated ML-ready datasets with needed data content, quality, format, and structure for each use case;
 * Develop, train, apply, and validate machine-learning models and other algorithms to transform Earth observation data into actionable information, particularly for Earth system feature detection;
 * Explore and share the best ways to apply modern techniques and access Earth Observation data with the aim of helping the community to develop, train, and apply the models;
 * Foster community development by encouraging and assisting EUMETSAT users in sharing commonly applicable parts of their applications in the form of how-to articles, code examples, infrastructure configurations, pre-trained models, datasets, etc.;
 * Take an active role in user communities and support training courses, hackathons, and other community-oriented means of spreading practical knowledge to EUMETSAT member states.