Research Software Engineer
To strengthen VITO's Environmental Intelligence unit, we are looking for several Research Software Engineers. You will help shape the next generation of GeoAI services, applying advances in artificial intelligence, foundation models and large-scale Earth observation processing. Our platforms support the European Commission, the European Space Agency and regional public authorities in their decisions on climate, food security, biodiversity and infrastructure.
We are looking for highly skilled software engineers and applied scientists with a broad foundation in data engineering and data science. The exact balance between platform engineering, large-scale data processing and applied machine learning will be shaped by your expertise and by project needs. Our end products must not only be innovative but also ready for trusted delivery---operable in regulated or access-restricted settings with strong requirements on robustness, traceability and information assurance. We therefore welcome applications from different profiles, including candidates who are stronger in some areas than others.
You join a talented team that operates at the forefront of European Space programmes, public policy and applied research. You work on systems with global visibility and concrete impact, with the freedom to bring your own ideas into platforms that are used well beyond our institute. We offer a working environment that combines the rigour of a research organisation with the pace of a modern software team.
Your responsibilities:
* Design, build and operate software components for geospatial AI, ranging from data ingestion and processing pipelines to interactive analytical applications and machine learning workflows.
* Develop and extend cloud-based platforms such as the Copernicus Data Space Ecosystem and Terrascope, contributing to open standards such as openEO and reusable building blocks.
* Apply state-of-the-art artificial intelligence techniques to Earth observation, including deep learning, geospatial foundation models and agentic systems that combine reasoning with geospatial data and tools.
* Translate requirements from thematic experts, end users and government stakeholders into robust, scalable and maintainable software.
* Apply engineering practices such as continuous integration, automated testing, infrastructure as code and machine learning operations to keep services reliable and efficient.
* Follow developments in software engineering, artificial intelligence and remote sensing closely, and bring relevant innovations into our platforms.