Machine Learning Engineer – AI Factory (Earth Sciences Department)

Employer

Barcelona Supercomputing Center

Location

Barcelona, Spain

Sector

Other

Atmospheric Sciences (AS)

Climate: Past, Present & Future (CL)

Earth and Space Science Informatics (ESSI)

Type

Full time

Level

Experienced

Open

Other

Preferred education

2 July 2025

Posted

Reference: 406_25_ES_CES_RE1

Job title: Machine Learning Engineer (RE1-2) – AI Factory (Earth Sciences Department)

About BSC

The 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 1000 staff from 60 countries.

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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 Barcelona Supercomputing Center ( BSC ) is seeking a Machine Learning Engineer to join the Earth Sciences department within the framework of the AI Factory initiative.

The AI Factory is a major European project aimed at accelerating the adoption and development of artificial intelligence across industry sectors that is deploying a comprehensive set of AI-focused services, including robust training, networking, and innovation support structures.

Its mission is to foster the uptake and effective use of AI, particularly among SME s and startups across participating countries, and to strengthen the European innovation ecosystem.

These services are powered by the AI-specific partition of the MareNostrum5 supercomputer, one of the most advanced infrastructures in Europe, designed to meet the evolving AI needs by harnessing the latest AI-oriented computing technologies.

Within the Earth Sciences department, the selected candidate will support the development and deployment of AI services related to climate change use and test cases, contributing to real-world applications and scientific advancements.

Additionally, the selected candidate will be coordinating the availability and integration of AI software, developed internally by consortium members or externally by third parties, on the MareNostrum5 AI partition, ensuring smooth support for the wider AI Factory user community.

This project is funded by the European Union's Recovery and Resilience Facility, in accordance with Council Regulation (EU) 2020/2094 of 14 December 2020, and regulated by Regulation (EU) 2021/241 of the European Parliament and of the Council of 12 February 2021, in the context of the "BSC AI Factory" project.

The BSC AI Factory project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101234399.

The JU receives support from the European Union's Horizon Europe Programme and Spain, Portugal, and Türkiye.

Support the documentation and curation of AI software employed in the AI Factory

Support the deployment and maintenance of AI software on MareNostrum5 AI partition

Design, implement, and optimize machine learning pipelines for environmental-related applications.

Collaborate with domain scientists and external users to develop AI solutions

Support users from the AI Factory in accessing and utilizing AI tools and services.

Participate in collaborative development within the AI Factory consortium.

Participate in technical reporting and scientific publications contributing to the documentation of the AI Factory software, with opportunities to be involved in academic publications and project reporting.

Requirements

Education

Bachelor's or Master's in Computer Science, Machine Learning, Data Science, Environmental Sciences, or a related field.

Essential Knowledge And Professional Experience

Strong programming skills in Python, with experience in machine learning libraries such as PyTorch, Tensorflow, and Scikit-learn.

Proven experience in developing and training machine learning models, particularly deep learning architectures.

Strong background in handling, analyzing, and validating large-scale datasets.

Experience working in a UNIX -based computational environment.

Additional Knowledge And Professional Experience

Familiarity with climate, weather, and Earth system datasets (NetCDF, Zarr).

Experience in high-performance computing ( HPC ) and parallelized machine learning workflows.

Proficiency in GPU -accelerated machine learning frameworks such as TensorFlow, RAPIDS , JAX , and/ or distributed training using Dask.

Understanding of climate and weather models.

Competences

Strong problem-solving and analytical skills, with the ability to optimize computational workflows.

Ability to work independently while collaborating effectively in a research environment.

Excellent communication skills, with a strong ability to document and present research findings.

Proficiency in written and spoken English.

Conditions

The position will be located at BSC within the Earth Sciences Department

We offer a full-time contract (37.5h/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: 23 paid vacation days plus 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

Applications procedure and process

All applications must be submitted via the BSC website and contain:

A full CV in English including contact details

A cover/motivation letter with a statement of interest in English, clearly specifying for which specific area and topics the applicant wishes to be considered.

Additionally, two references for further contacts must be included.

Applications without this document will not be considered.

Development of the recruitment process

The selection will be carried out through a competitive examination system ("Concurso-Oposición").

The Recruitment Process Consists Of Two Phases:

Curriculum Analysis: Evaluation of previous experience and/or scientific history, degree, training, and other professional information relevant to the position.

– 40 points

Interview phase: The highest-rated candidates at the curriculum level will be invited to the interview phase, conducted by the corresponding department and Human Resources.

In this phase, technical competencies, knowledge, skills, and professional experience related to the position, as well as the required personal competencies, will be evaluated.

– 60 points.

A minimum of 30 points out of 60 must be obtained to be eligible for the position.

The recruitment panel will be composed of at least three people, ensuring at least 25% representation of women.

In accordance with OTM -R principles, a gender-balanced recruitment panel is formed for each vacancy at the beginning of the process.

After reviewing the content of the applications, the panel will begin the interviews, with at least one technical and one administrative interview.

At a minimum, a personality questionnaire as well as a technical exercise will be conducted during the process.

The panel will make a final decision, and all individuals who participated in the interview phase will receive feedback with details on the acceptance or rejection of their profile.

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

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

For more information, please follow this link.

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