Research Software Engineer - Forecast-in-a-Box Developer

Destination Earth is developing Digital Twins of the Earth system, combining high-resolution numerical and machine learning (ML) models. In this context, the Forecast-in-a-Box encapsulates a portable, reproducible and scalable environment that supports experimentation, deployment and downstream product generation for a range of ML models, delivering a fully packaged ML-based modelling chain to users. This builds on ECMWF's software stack, which also underpins Destination Earth's Digital Twin Engine.

In this role, you will contribute to the development and implementation of the execution workflows that enable the Forecast-in-a-Box to interface seamlessly with ECMWF's operational forecasting and post-processing pipelines. This includes ensuring robustness, scalability and performance across distributed high-performance computing and cloud environments and supporting the integration of new post-processing pipelines within the framework.

Working closely with ECMWF scientists, software engineers and Digital Twin Engine developers, you will support the integration of ML models and outputs into coherent, automated workflows. You will contribute to ensuring these workflows are reproducible, maintainable, operationally viable and integrate seamlessly within the Earthkit ecosystem.

The position sits in the Data Processing Services Team in the Development Section in the Forecast and Services Department. You will join a dynamic group working on AI/ML workflows, distributed computing and large-scale data processing. The team plays a central role in evolving ECMWF's operational post-processing framework and in connecting research innovation with production-grade forecasting systems., * As part of a team, design, develop and contribute to the evolution of the Forecast-in-a-Box framework.

• Collaborate with Digital Twin Engine developers and ECMWF partners to align Forecast-in-a-Box execution workflows with DestinE standards and services.
• Integrate ML models and post-processing components into the Forecast-in-a-Box environment, in alignment with ECMWF's operational post-processing framework.
• Adapt ML modelling workflows to diverse computing environments, including resource-constrained operational settings.
• Develop technical documentation, reproducible examples and training materials to support knowledge transfer and long-term sustainability.
• Participate in technical workshops and training activities linked to DestinE and related initiatives.
• Contribute to ECMWF's open-source software ecosystem, including projects such as Anemoi and Earthkit.

Do you have experience in UNIX?, Do you have a Bachelor's degree?, * Excellent analytical and problem-solving skills with a proactive, continuous improvement approach.

• Initiative and ability to work collaboratively, with other ECMWF teams and external collaborators, but also able to work independently.
• Ability to maintain a supportive and user-focused approach.
• Good interpersonal and communication skills.
• Willingness to occasionally travel within Europe.
• Dedication, passion, and enthusiasm to succeed both individually and across teams of developers.
• Highly organised with the capacity to work on a diverse range of tasks to tight deadlines.

Your profile

• 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 in developing and maintaining object-oriented software in Python within structured or modular frameworks.

• Experience collaborating with developers and end users to gather requirements, incorporate feedback and plan technical developments.

• Experience contributing to large-scale software projects, preferably open-source and/or involving multiple interoperable components.

• Experience designing or implementing machine learning workflows is an advantage.

• Experience in weather or climate forecasting post-processing and the handling of complex derived products is an advantage.

• Experience developing software for high-availability operational environments is an advantage.

• Competence in software engineering, preferably in Python.

• Demonstrated ability of programming in UNIX/Linux systems.

• Ability to write software in a distributed computing or scientific computing environment.

• Knowledge of ECMWF's open-source stack, particularly Earthkit, is an advantage.

• Knowledge of Machine Learning workflows and processing on GPUs is an advantage.

Candidates must be able to work effectively in English; knowledge of one of the Centre's other working languages (French or German) is an advantage.

The European Centre for Medium-Range Weather Forecasts (ECMWF) is a world leader in Numerical Weather Predictions providing high-quality data for weather forecasts and environmental monitoring. As an intergovernmental organisation, we collaborate internationally to serve our members and the wider community with global weather predictions, data and training activities that are critical to contribute to safe and thriving societies. The success of our activities depends on the funding and partnerships of the 35 Member and Co-operating States who provide the support and direction of our work. Our talented staff together with the international scientific community, and our powerful supercomputing capabilities, are the core of a 24/7 research and operational centre with a focus on medium and long-range predictions. We also hold one of the largest meteorological data archives in the world. ECMWF has also developed a strong partnership with the European Union and has been entrusted with the implementation and operation of the Destination Earth Initiative and the Climate Change and Atmosphere Monitoring Services of the Copernicus Programme and the Strengthening Early Earning in Africa (SEWA) Programme. Other areas of work include High Performance Computing and the development of digital tools that enable ECMWF to extend provision of data and products covering weather, climate, air quality, fire and flood prediction and monitoring. Our vision: The strength of a common goal Our mission: Deliver global numerical weather predictions focusing on the medium-range and monitoring of the Earth system to and with our Member States ECMWF is a multi-site organisation, with its headquarters in Reading, UK, a data centre in Bologna, Italy, and a large presence in Bonn, Germany, as a central location for our EU-related activities. ECMWF is internationally recognised as the voice of expertise in numerical weather predictions for forecasts and climate science. www.ecmwf.int About DestinE | Destination Earth ECMWF is one of the entities entrusted with implementing the DestinE initiative of the European Commission, alongside ESA and EUMETSAT, and works closely with over 100 partner institutions across Europe. DestinE delivers high-resolution, configurable digital twins of the Earth system that simulate past, present and plausible future environmental conditions and enable "what-if" scenario exploration. ECMWF is responsible for the delivery of these digital twins and of the Digital Twin engine, the software infrastructure needed to power the digital twins on the European HPC Joint Undertaking (EuroHPC) and ECMWF's supercomputers and to handle and enable access to their data via the DestinE infrastructure, as well as for a range of Artificial Intelligence/ Machine Learning (AI/ML) activities. These include developments towards an ML Earth system model and a range of AI solutions that increase system interactivity and usability of digital twin data. The third phase of DestinE (June 2026 June 2028) marks the transition of the Climate Change Adaptation and Weather-induced Extremes Digital Twins, together with the Digital Twin Engine, into sustained operations. During this phase, the focus will be on consolidating, operating, and further evolving these key elements, as well as on maturing the AI Earth-system model components and AI-based solutions developed in phase 2. The Climate DT is implemented by a partnership led by CSC, currently involving 12 leading climate institutions, supercomputing centres, national meteorological services, academia and industrial partners, through a contract procured by ECMWF. For more about DestinE and the Climate DT, seehttps://destine.ecmwf.intandhttps://destination-earth.eu., Grade remuneration: The successful candidates will be recruited according to the scales of the Co-ordinated Organisations. Details of salary scales and allowances are available on the ECMWF website at www.ecmwf.int/en/about/jobs. Starting date: as soon as possible. Candidates are expected to relocate to the duty station, either Bonn, Germany, or Reading, UK. As a multi-site organisation, ECMWF has adopted a hybrid organisation model which allows flexibility to staff to mix office working and teleworking, including away from the duty station (within the area of our member states and co-operating states). Interviews by videoconference (MS Team) are expected to take place shortly after the vacancy closing date. Successful applicants and members of their family forming part of their households will be exempt from immigration restrictions., At ECMWF, we consider an inclusive environment as key for our success. We are dedicated to ensuring a workplace that embraces diversity and provides equal opportunities for all, without distinction as to race, gender, age, marital status, social status, disability, sexual orientation, religion, personality, ethnicity and culture. We value the benefits derived from a diverse workforce and are committed to having staff that reflect the diversity of the countries that are part of our community, in an environment that nurtures equality and inclusion. Applications are invited from nationals from ECMWF Member States and Co-operating States as well as nationals of European Union member states. In these exceptional times, we also welcome applications from Ukrainian nationals for this vacancy. Applications from nationals from other countries may be considered in exceptional cases. ECMWF Member States and Co-operating States are: Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, Norway, North Macedonia, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and the United Kingdom.   You must create an Indeed account before continuing to the company website to apply