As a Machine Learning Scientist/Engineer, you will develop and train data-driven weather models based on our large data archive. You will have the unique opportunity to implement innovative, data-driven approaches for weather forecasting for Switzerland.
This is how you can contribute
- Develop and implement machine learning algorithms with a focus on data-driven approaches to weather forecasting
- Contribute to the development of the MeteoSwiss-wide MLOps platform, data pre-processing, cleansing and feature engineering
- Collaborate in an interdisciplinary team of meteorologists and computer scientists to integrate machine learning models with traditional methods of weather forecasting
- Collaborate with international institutions (ECMWF) and other national weather services in international projects to develop ML models for global and regional weather forecasting
This makes you unique
- University degree (MSc or PhD) in data science, computer science, applied mathematics or a related field
Proven experience in developing and implementing machine learning algorithms and data science concepts and methods - Strong programming skills in Python and familiarity with ML frameworks (TensorFlow, PyTorch, Keras, etc.)
- Experience in handling and processing large data sets or experience in high-performance computing (HPC) is an advantage
- You are creative, solution-oriented and have excellent communication skills and the ability to work with interdisciplinary teams
- Good knowledge of spoken and written English and knowledge of an official language
What sets us apart
The Swiss Federal Office for Meteorology and Climatology MeteoSwiss is the Swiss National Weather Service. We record and forecast weather and climate in Switzerland and thus make a sustainable contribution to the well-being of the community and to the benefit of industry, science and the environment.
Federal offices of the Federal Department of Home Affairs (FDHA) are committed to good working conditions and protecting the health of their employees and have been awarded the Friendly Work Space label.