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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Scientist - **Company:** ECMWF - **Location:** Bonn, Germany (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Machine Learning, Azure Machine Learning, Software Engineering, Software Systems, Supercomputing, Digital Twin, Graphics Processing Unit (GPU), Software Library - **Published:** October 26, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d74cd4a34de78c58 ## About the Role * Excellent interpersonal and communication skills with the ability to collaborate effectively across interdisciplinary teams (machine learning engineers and scientists, domain scientists, operations) and external partners * Ability to work on and contribute effectively to large software projects following modern coding practices, including writing tests and reviewing code * Experience with the development and evaluation of machine learning models, including model design, implementation, training, and scaling * Experience with the application of machine learning in the wider context of Earth system modelling would be an advantage * Experience in designing for and optimizing performance of machine learning tools for training and inference on single GPUs and large HPCs would be an advantage Your profile - Education, experience, knowledge and skills (including language) * Advanced university degree (EQ7 level or above) in a physical, mathematical, data/machine learning or environmental science, or equivalent professional experience * Experience in machine learning and/or machine learning engineering, including best practices for software development * Experience in Earth system modelling is desirable * Experience in HPC or large data science projects is desirable Candidates must be able to work effectively in English. A good knowledge of one of the Centre's other working languages (French or German) is an advantage., Interviews by videoconference (MS Teams) interviews will be conducted in English and are expected to take place approximately a month after the closing date. ## Description We are looking for a highly motivated Machine Learning Scientist to help develop world-leading machine learning models for weather and climate and ensure these are built on an efficient, scalable and sustainable software infrastructure. The work requires technical expertise to create state-of-the-art and sustainable machine learning models but also to develop the required underlying software infrastructure. It necessitates excellent soft skills to work seamlessly in an international, interdisciplinary, and highly diverse working environment. The role will, in particular, support the scientific and technical development of a machine-learned Earth system model and contribute to Anemoi, the software library for machine learning-based weather forecasting and Earth system modelling developed by ECMWF and its member states. It will also contribute the maintenance of the WeatherGenerator code base that is used in the EarthGenerator project and help increase the HPC efficiency of the model. The position will also support the CLAIMA project, which develops infrastructure for machine learning climate models, and wider developments around the WeatherGenerator. About the Team The position will be located in the Machine Learning Modelling Team in the Earth System Modelling Section of the Research Department. The Machine Learning Modelling Team focuses on the development and application of machine learning for Earth system modelling. This includes developments for ECMWF's operational Artificial Intelligence Forecasting System (AIFS), machine learning models to represent Earth system components such as ocean, sea ice and land, and methodological developments such as foundation modelling and generative machine learning. The advertised position will work in very close collaboration with physical modellers and several other teams and sections within ECMWF. It will also have a direct impact on operational weather prediction at ECMWF and the creation of Digital Twins as part of Destination Earth. At ECMWF, you will find a passionate community, collectively aiming to build world-leading global Earth system models for numerical weather prediction. This effort supports ECMWF's strategy of producing cuttingedge science and world-leading weather predictions and monitoring of the Earth system. About the Project This role is funded through two major European initiatives: Destination Earth (DestinE) and EarthGenerator. Destination Earth, an initiative of the European Commission, is developing Digital Twins of the Earth and a machine-learned Earth system model for weather and climate applications. This includes learned ocean, wave, sea-ice, land surface and hydrology models developed using Europe's largest EuroHPC supercomputers. The WeatherGenerator Horizon Europe project builds a European foundation model for weather and climate. The EarthGenerator Horizon Europe project extends the concept of the WeatherGenerator and explores foundation models for Earth sciences that can be applied to long prediction timescales from multiple years to decades. The CLAIMA Horizon Europe project will compare different machine learning models for use cases in the area of climate modelling., You will: * Contribute to an efficient and sustainable software infrastructure for world-leading machine learning models at ECMWF and the ECMWF Member and Co-operating States * Support the evolution of Anemoi while ensuring that the code meets the highest standards and is long-term sustainable * Support maintenance and improvements to the WeatherGenerator code base, ensuring its long-term viability * Explore new machine learning architectures and capabilities for Earth system modelling for operational weather predictions and Earth system modelling more generally * Implement and evaluate new models and training protocols for weather forecasting and Earth system modelling in the context of both AIFS and the WeatherGenerator