Data/Ml Engineer For Regional Ai Weather/Climate Forecasting Datasets

Barcelona Supercomputing Center; Barcelona; Presencial; EUR 55.000 - 75.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Restaurant tickets

Private health insurance

Relocation support

Descripción de la vacante

Barcelona Supercomputing Center (BSC) seeks a Data/ML Engineer to develop AI-ready weather/climate datasets and reproducible pipelines for regional forecasting. You will curate high-resolution data, transform it for ML training, and ensure reproducibility and scalability on HPC and AI platforms.

The role requires strong Python and data-processing experience, UNIX/Linux skills, and collaboration with an international consortium of meteorological and research institutions.

Formación

• Bachelor's degree in Computer Science, Physics, Environmental/Atmospheric Science, or related field.
• A Master's or PhD in a relevant area is highly valued.

Responsabilidades

• Curate and assess regional analyses and datasets for training E2E AI forecasting.
• Design and maintain reproducible ML data pipelines.
• Implement automated tests and CI/CD for data workflows.
• Support deployment and validation on HPC/AI infrastructure.

Conocimientos

Python

ETL pipelines

Xarray

NetCDF/GRIB/Zarr

UNIX/Linux

HPC (Slurm)

GPU workflows

Educación

Bachelor's degree in CS/Physics/Env/Atmos Sci

Master's or PhD valued

Herramientas

Docker

Podman

Git

Slurm

CI/CD

HPC workflows

Linux

Descripción del empleo

Job Reference421_26_ES_CES_RE2PositionData/ML Engineer for Regional AI Weather/Climate Forecasting Datasets (RE1-2)Closing DateThursday, 22 October, ****Reference:421_26_ES_CES_RE2Job title:Data/ML Engineer for Regional AI Weather/Climate Forecasting Datasets (RE1-2)

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.

Look At The BSC Experience

BSC-CNS YouTube Channel

Let's stay connected with BSC Folks!

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.

In instances of equal merit, the incorporation of the under-represented sex will be favoured.

We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.

If you consider that you do not meet all the requirements, we encourage you to continue applying for the job offer.

We value diversity of experiences and skills, and you could bring unique perspectives to our team.

Context And Mission

The 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.

The role involves close collaboration with an international consortium of European meteorological and research institutions.

Key Duties

• Curate and assess regional analyses, forecasts, and reanalyses for training and evaluating the regional AI forecasting system
• Design, build, and maintain reproducible ML data pipelines that transform raw simulation and observational data into Anemoi-compatible datasets
• Implement automated testing and CI/CD pipelines for the data-processing workflows
• Support deployment and validation of data pipelines on HPC and AI Factory infrastructure, including scalability and performance testing
• Collaborate with the international consortium and document pipelines to ensure reproducibility and traceability

Requirements

• EducationBachelor'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 Experience

• Strong programming skills in Python and experience building data-processing/ETL pipelines.
• Experience handling scientific data formats such as NetCDF, GRIB, Zarr, and tools such as Xarray, CDO/NCO.
• Experience preparing datasets for machine-learning training pipelines, ideally in Earth, weather, or climate sciences.
• Familiarity with UNIX/Linux environments and scripting languages.
• Experience with high-performance computing (HPC) environments, including job schedulers (e.G. Slurm) and GPU-based workflows.

Additional Knowledge and Professional Experience

• Familiarity with the Anemoi ecosystem (anemoi-datasets, anemoi-training) or similar ML-ready NWP dataset frameworks will be highly valued.
• Knowledge of NWP/reanalysis datasets (e.G. 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.

Competences

• Ability to work independently and within an international, multi-partner consortium to achieve project goals.
• Strong problem-solving skills and attention to detail.
• Excellent communication skills to collaborate effectively with interdisciplinary teams.

Conditions

The position will be located at BSC within the Earth Sciences DepartmentWe offer a full-time contract (35h/week), a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible 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

Salary: we offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona

Starting date: As soon as possible

Deadline

The vacancy will remain open until a suitable candidate has been hired.

At BSC, we seek continuous improvement in our recruitment processes.

For any suggestions or comments/complaints about our recruitment processes, please contact ******

OTM-R principles for selection processes

BSC-CNS is committed to the principles of the Code of Conduct for the Recruitment of Researchers of the European Commission and the Open, Transparent and Merit-based Recruitment principles (OTM-R).

This is applied for any potential candidate in all our processes, for example by creating gender-balanced recruitment panels and recognizing career breaks etc.

BSC-CNS is an equal opportunity employer committed to diversity and inclusion.

We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law.