Research Software Engineer - ML Framework Development

at  ECMWF

THE TEAM

The role sits in the Data Processing Services Team, within the Development Section in the Forecasts and Services Department. The team ensures the scalability, performance, and robustness of the operational weather forecasting pipeline. Effort is dedicated to navigating challenges posed by future model upgrades. This is done by exploring new technology, such as accelerators and novel storage hardware, and new algorithmic methodologies, including machine learning. We aim to be ahead of the curve, in order to maintain ECMWFs world-leading position for global weather prediction.

EDUCATION

• Advanced university degree (EQ7 level or above) or equivalent professional experience in computer science or engineering, computational science, physics or natural sciences, mathematics, or a related discipline.

EXPERIENCE

• Demonstrated experience developing object-oriented software in Python
• Experience with dealing with users, gather feedback and plan developments
• Experience contributing to large-scale software projects, preferably open-source and/or involving multiple software components
• Capability to develop scientific software to process large datasets would be desirable
• Experience in machine learning workflows would be an advantage
• Experience developing software for high-availability operational environments would be an advantage

KNOWLEDGE AND SKILLS

• Competence in Object-Oriented Analysis and Design, preferably in Python
• Strong knowledge of software lifecycle maintenance
• Demonstrated ability programming in UNIX/Linux systems
• Ability to write software in a distributed computing or scientific computing environment

THE ROLE

We are in search of a highly motivated Research Software Engineer (A2) to work with ECMWF’s Member States on the next generation of machine-learned weather forecasting models. This role is an integral part of a dynamic team, consisting of scientists and software engineers contributing to building ECMWF’s next generation of weather forecasting systems.
At ECMWF, you will join a passionate community collectively aiming to bring novel technology and science to the cutting-edge of numerical weather prediction. With the recent breakthrough in Artificial Intelligence (AI) and the progress made in AI-driven weather forecasting, it becomes clear that AI will play a key role in the next generation of forecasting systems. To this end, ECMWF built a dedicated multi-disciplinary group to tackle these challenges. ECMWF has been the first operational weather centre to publish results of its own global machine-learned weather model the Artificial Intelligence Forecasting System (AIFS).
We are working with our Member States to build a high-level machine learning framework to train data-driven weather forecasting models, called Anemoi https://anemoi-docs.readthedocs.io. For ECMWF, the AIFS is one possible product from this system, which will enable meteorological organisations to provide data sources and recipes to train forecasting models. This concept has already been demonstrated https://www.ecmwf.int/en/about/media-centre/aifs-blog/2024/data-driven-regional-modelling .
In this role, you will work closely with our Member States and provide them with support to build machine-learned forecasting models tailored to their needs. You will also gather feedback and requirements to improve the ECMWF software stack. The position may require frequent travels to our Member States and work closely with their teams to develop and improve their machine-learned tools and workflows.

MAIN DUTIES AND RESPONSIBILITIES

• Actively contribute to the ECWMF open-source software stack, with a big focus on machine learning
• Be a contact point with our Member and Cooperating States for machine-learning software and workflows
• Promote the ECMWF software stack to Member States and continuously gather requirements for future releases
• Provide support to Member States to build their machine learned weather forecasting models