Machine Learning Scientist and Engineer for Weather and Climate

The Center for Climate Systems Modeling (C2SM) at ETH Zurich, in partnership with the Federal Office of Meteorology (MeteoSwiss), is pioneering innovative methods to leverage machine learning for numerical weather forecasting and climate modeling.

The HiRAD-Gen project focuses on creating cutting-edge generative machine-learning models to transform coarse-resolution atmospheric data into high-resolution outputs. By utilizing advanced techniques such as Corrector-Diffusion models and fine-tuned foundation models, HiRAD-Gen aims to deliver precise and computationally efficient high-resolution forecasts, significantly lowering computational costs while enhancing model reliability.

We are hiring for two positions: a Machine Learning Engineer to develop the software infrastructure and the product and a Machine Learning Scientist to focus more on the ML model development.

• 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.) and ML Ops
• 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

• Unique opportunities to develop state of the art Machine Learning system
• You will join a dynamic team operating at the intersection of cutting-edge research and real-world applications
• We are committed to fostering a diverse and inclusive workplace and offer flexible working arrangements to support work-life balance for all team members.