This is how you can contribute

• Deliver MeteoSwiss's technical expertise in an international cooperation project focused on improving meteorological forecasts in South Asia
• Apply machine learning (ML) methods to improve local precipitation forecasts
• Develop and operationalize practical solutions for the use of ML methods in collaboration with national meteorological services in the region
• Cooperate with international project partners such as the University of Oxford, the World Meteorological Organization, and national weather services in the region, and exchange expertise on ML methods
• Conduct regular business trips to South Asia, give presentations at conferences, publish in professional journals and grey literature, and actively disseminate knowledge

This makes you unique

• Master's degree in computer science, mathematics, data science, or the natural sciences (e.g., physics, meteorology, climatology)
• In-depth expertise in processing and curating meteorological and climatological data (e.g., netCDF, GRIB) as well as in designing data pipelines
• Proven, multi-year expertise in software development and application deployment, including container technologies (Docker), CI/CD, and scalable systems, ideally in cloud environments
• Experience in using machine learning with Python (e.g., PyTorch, TensorFlow, or JAX) as well as in the deployment and operation of ML inference systems (MLOps, monitoring, versioning)
• Strong intercultural competence, a solution-oriented and self-reliant mindset, , as well as the ability to work confidently and with enthusiasm within a team and with a diverse range of international stakeholders from administration, academia, and practice
• Excellent oral and written proficiency in one official language and good proficiency in a second; outstanding English language skills

In a nutshell

MeteoSwiss is actively involved in international cooperation and supports partner meteorological services in building their capacity. In this context, MeteoSwiss acts as a “peer advisor” to partners on topics such as measurement networks, modeling, service development, as well as organizational structures and their environments. In your role as an ML expert and as part of a cross-departmental team, you will contribute significantly to implementing this effort.