Job Reference: 421_26_ES_CES_RE2Position: Data/ML Engineer for Regional AI Weather/Climate Forecasting Datasets (RE1-2)Closing Date: Thursday, 22 October, ****Reference: 421_26_ES_CES_RE2Job title: Data/ML Engineer for Regional AI Weather/Climate Forecasting Datasets (RE1-2)About BSCThe Barcelona Supercomputing Center
- Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D; into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over ***
* staff from 60 countries. We are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research. Context And MissionThe successful candidate will join the Computational Earth Sciences group within the Earth Sciences department to contribute to projects within the Destination Earth (DestinE) initiative. DestinE is a European Union flagship programme building high-precision digital replicas 'Digital Twins' of the Earth system to support climate adaptation and extreme-weather preparedness. The candidate will work to develop AI-ready datasets and data pipelines that support the training and evaluation of regional AI weather and climate forecasting systems,



built on open-source frameworks such as Anemoi. This includes curating and preparing high-resolution simulation and observational data, building reproducible pipelines to make these datasets machine-learning-ready, and supporting their deployment and validation on high-performance and AI-oriented computing infrastructure. Key DutiesCurate and assess regional analyses, forecasts, and reanalyses for training and evaluating the regional AI forecasting systemDesign, build, and maintain reproducible ML data pipelines that transform raw simulation and observational data into Anemoi-compatible datasetsImplement automated testing and CI/CD pipelines for the data-processing workflowsSupport deployment and validation of data pipelines on HPC and AI Factory infrastructure, including scalability and performance testingCollaborate with the international consortium and document pipelines to ensure reproducibility and traceabilityRequirementsEducationBachelor's degree in Computer Science, Physics, Environmental/Atmospheric Science, or a related discipline. A Master's degree or PhD in a relevant field will be highly valued.
Essential Knowledge and Professional ExperienceStrong programming skills in Python and experience building data-processing/ETL pipelinesExperience handling scientific data formats such as NetCDF, GRIB, Zarr, and tools such as Xarray, CDO/NCOExperience preparing datasets for machine-learning training pipelines,



ideally in Earth, weather, or climate sciencesFamiliarity with UNIX/Linux environments and scripting languagesExperience with high-performance computing (HPC) environments, including job schedulers (e.
Slurm) and GPU-based workflowsAdditional Knowledge and Professional ExperienceFamiliarity with the Anemoi ecosystem (anemoi-datasets, anemoi-training) or similar ML-ready NWP dataset frameworks will be highly valued.
ERA5, CERRA, regional model output) and data-quality assessment.
Experience with CI/CD tools, containerization (Docker/Podman) and automated testing.
Experience with version control systems like Git.
Fluency in English is essential.
Proficiency in Spanish and other European languages would be advantageous.
CompetencesAbility to work independently and within an international, multi-partner consortium to achieve project goals.

We offer
a full-time contract (35h/week), a good working environment, a highly stimulating environment with state-of-the-art infrastructure, versátil

working hours
, extensive training plan, restaurant tickets, private health insurance, support to the relocation procedures. Duration: Open-ended contract due to technical and scientific activities linked to the project and budget duration. Holidays: 22 days of holidays + 6 personal days + 24th and 31st of December per our collective agreement. Evaluation of previous experience and/or scientific history, degree, training, and other professional information relevant to the position.
The recruitment panel will be composed of at least three people, ensuring at least 25% representation of women. After reviewing the content of the applications, the panel will begin the interviews, with at least one technical

📌 Seleccionamos Data Architect (Madrid)
🏢 Barcelona Supercomputing Center
📍 Madrid