Machine Learning Operations Engineer - MLOps (RE 1-2)

Overview

Job Reference: 407_25_ES_CES_RE1

Position: Machine Learning Operations Engineer - MLOps (RE 1-2) – AI Factory (Earth Sciences Department)

Closing Date: Sunday, 01 March, ****

Reference

407_25_ES_CES_RE1

Job Title

Machine Learning Operations Engineer - MLOps (RE 1-2) – 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 **** staff from 60 countries.

Context and Mission

The Barcelona Supercomputing Center (BSC) is seeking a Machine Learning Operations Engineer (MLOps) 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. It deploys 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 SMEs 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, designed to meet evolving AI needs by harnessing the latest AI-oriented computing technologies.

Within the Earth Sciences department, the selected MLOps Engineer will support the development, deployment, and operationalization of AI services related to Earth Sciences applications. This includes contributing to real-world applications with direct scientific and societal impact. The candidate will be responsible for managing the integration and availability of AI software tools, developed internally by consortium partners or externally by third parties, on the MareNostrum5 AI partition. This involves ensuring compatibility, performance, and scalability of AI workloads on the MN5 infrastructure and providing technical support to the broader AI Factory user community. The role will involve close collaboration with researchers, developers, and system administrators to streamline workflows, automate deployment pipelines, and maintain robust, reproducible AI environments using best practices in MLOps.

Key Duties

Manage and maintain AI software stacks and tools on the MN5 supercomputer.

Support the deployment and scaling of AI workflows for users, particularly in environmental applications.

Collaborate with the group and consortium members, as well as external developers, to integrate new software tools and ensure compatibility.

Develop and maintain CI/CD pipelines and containerization workflows (e.g., Docker, Singularity).

Optimize MLOps workflows, including model versioning, monitoring, lifecycle management, and troubleshooting.

Requirements

Education

Bachelor\'s or Master\'s degree in computer science, artificial intelligence or similar

Essential Knowledge And Professional Experience

Solid experience in MLOps, DevOps, or a related software engineering role.

Proficiency with AI/ML frameworks (e.g., TensorFlow, PyTorch) and tools for workflow orchestration.

Strong knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).

Experience in scaling generative models and deploying them in production environments

Competences

Experience working in HPC or cloud-based environments will be valued.

Familiarity with climate science datasets is desirable.

Good communication skills and the ability to work in an international, multidisciplinary team.

Fluency in spoken and written 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: 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

Applications procedure and process

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

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.

Deadline

The vacancy will remain open until a suitable candidate has been hired. Applications will be regularly reviewed and potential candidates will be contacted.

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.

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