Job Reference: 406_25_ES_CES_RE1 Position: Machine Learning Engineer (RE1-2) – AI Factory (Earth Sciences Department)
Closing Date: Sunday, 01 March, ****
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, and hosts the European HPC ecosystem.
The mission of BSC is to research, develop and manage information technologies to facilitate scientific progress.
BSC combines HPC service provision and R&D into computer and computational science under one roof, with over **** staff from 60 countries.
Context and Mission: The Barcelona Supercomputing Center (BSC) is seeking a Machine Learning Engineer to join the Earth Sciences department within the AI Factory initiative.
The AI Factory accelerates adoption and development of AI across industry sectors, deploying AI-focused services including training, networking, and innovation support.
The MareNostrum5 AI partition provides the computing backbone for these services.
The selected candidate will support AI services related to climate change use cases, coordinate availability and integration of AI software on MareNostrum5, and ensure smooth support for the AI Factory user community.
Responsibilities
Support the documentation and curation of AI software employed in the AI Factory
Support the deployment and maintenance of AI software on the 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, state-of-the-art infrastructure, flexible working hours, extensive training plan, restaurant tickets, private health insurance, and support for relocation procedures
Duration: Open-ended contract due to project and budget considerations
Holidays: 22 days of holidays + 6 personal days + 24th and 31st of December
Salary: Competitive salary commensurate with qualifications and experience, aligned with Barcelona cost of living
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 the area and topics of interest; two references for further contact must be included
Recruitment process and equal opportunity
The selection will be carried out through a competitive examination system (Concurso-Oposición).
The process consists of two phases: Curriculum Analysis (40 points) and Interview phase (60 points).
A minimum of 30 points in the interview is required.
The recruitment panel will include at least three people with gender representation.
BSC adheres to OTM-R principles and promotes gender-balanced recruitment panels.
All participants will receive feedback after interviews.
For suggestions or complaints about recruitment processes, please contact ******.
For more information follow this link.
Deadline: The vacancy remains open until a suitable candidate is hired; applications are regularly reviewed.
OTM-R and equal opportunity
BSC-CNS is committed to the Code of Conduct for the Recruitment of Researchers and Open, Transparent and Merit-based Recruitment (OTM-R).
We are an equal opportunity employer and consider all qualified applicants regardless of protected characteristics.
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