Machine Learning Engineer (Re1-2) – Ai Factory (Earth Sciences Department)
Barcelona Supercomputing CenterSpain7 hours ago
Full-timeInformation Technology
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Overview Job Reference: 406_25_ES_CES_RE1Position: Machine Learning Engineer (RE1-2) – AI Factory (Earth Sciences Department)Closing Date: Sunday, 01 March, ****Reference: 406_25_ES_CES_RE1Job 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 FactorySupport the deployment and maintenance of AI software on the MareNostrum5 AI partitionDesign, implement, and optimize machine learning pipelines for environmental-related applicationsCollaborate with domain scientists and external users to develop AI solutionsSupport users from the AI Factory in accessing and utilizing AI tools and servicesParticipate in collaborative development within the AI Factory consortiumParticipate 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 reportingRequirements EducationBachelor's or Master's in Computer Science, Machine Learning, Data Science, Environmental Sciences, or a related fieldEssential Knowledge and Professional ExperienceStrong programming skills in Python, with experience in machine learning libraries such as PyTorch, TensorFlow, and Scikit-learnProven experience in developing and training machine learning models, particularly deep learning architecturesStrong background in handling, analyzing, and validating large-scale datasetsExperience working in a UNIX-based computational environmentAdditional Knowledge and Professional ExperienceFamiliarity with climate, weather, and Earth system datasets (NetCDF, Zarr)Experience in high-performance computing (HPC) and parallelized machine learning workflowsProficiency in GPU-accelerated machine learning frameworks such as TensorFlow, RAPIDS, JAX, and/or distributed training using DaskUnderstanding of climate and weather modelsCompetencesStrong problem-solving and analytical skills, with the ability to optimize computational workflowsAbility to work independently while collaborating effectively in a research environmentExcellent communication skills, with a strong ability to document and present research findingsProficiency in written and spoken EnglishConditions The position will be located at BSC within the Earth Sciences DepartmentWe 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 proceduresDuration: Open-ended contract due to project and budget considerationsHolidays: 22 days of holidays + 6 personal days + 24th and 31st of DecemberSalary: Competitive salary commensurate with qualifications and experience, aligned with Barcelona cost of livingStarting date: As soon as possibleApplications procedure and process All applications must be submitted via the BSC website and contain:A full CV in English including contact detailsA 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 includedRecruitment 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 ****** more information follow this link.
Deadline: The vacancy remains open until a suitable candidate is hired; applications are regularly reviewed.OTM-R and equal opportunityBSC-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.
#J-*****-Ljbffr
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 FactorySupport the deployment and maintenance of AI software on the MareNostrum5 AI partitionDesign, implement, and optimize machine learning pipelines for environmental-related applicationsCollaborate with domain scientists and external users to develop AI solutionsSupport users from the AI Factory in accessing and utilizing AI tools and servicesParticipate in collaborative development within the AI Factory consortiumParticipate 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 reportingRequirements EducationBachelor's or Master's in Computer Science, Machine Learning, Data Science, Environmental Sciences, or a related fieldEssential Knowledge and Professional ExperienceStrong programming skills in Python, with experience in machine learning libraries such as PyTorch, TensorFlow, and Scikit-learnProven experience in developing and training machine learning models, particularly deep learning architecturesStrong background in handling, analyzing, and validating large-scale datasetsExperience working in a UNIX-based computational environmentAdditional Knowledge and Professional ExperienceFamiliarity with climate, weather, and Earth system datasets (NetCDF, Zarr)Experience in high-performance computing (HPC) and parallelized machine learning workflowsProficiency in GPU-accelerated machine learning frameworks such as TensorFlow, RAPIDS, JAX, and/or distributed training using DaskUnderstanding of climate and weather modelsCompetencesStrong problem-solving and analytical skills, with the ability to optimize computational workflowsAbility to work independently while collaborating effectively in a research environmentExcellent communication skills, with a strong ability to document and present research findingsProficiency in written and spoken EnglishConditions The position will be located at BSC within the Earth Sciences DepartmentWe 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 proceduresDuration: Open-ended contract due to project and budget considerationsHolidays: 22 days of holidays + 6 personal days + 24th and 31st of DecemberSalary: Competitive salary commensurate with qualifications and experience, aligned with Barcelona cost of livingStarting date: As soon as possibleApplications procedure and process All applications must be submitted via the BSC website and contain:A full CV in English including contact detailsA 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 includedRecruitment 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 ****** more information follow this link.
Deadline: The vacancy remains open until a suitable candidate is hired; applications are regularly reviewed.OTM-R and equal opportunityBSC-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.
#J-*****-Ljbffr
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