Job Reference: 331_26_DIR_IBD_Dev Ops
Closing Date: Saturday, 31 October, 2026
Job title
AI Factory Engineer - Dev Ops/MLOps
About BSC
The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses Mare Nostrum, 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 Euro HPC 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.
Equity, Diversity and Inclusion
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 AI Factory is scaling the adoption of AI solutions from experimentation to production. To support this growth, we are looking for a Dev Ops/MLOps Engineer who will provide the operational foundations required to deploy, monitor, maintain, and scale AI services reliably and efficiently. The role will be responsible for implementing deployment pipelines, automation, monitoring, environment management, and operational best practices for machine learning and generative AI systems. Working closely with AI engineers, platform teams, infrastructure specialists, and security teams, the successful candidate will help ensure that AI solutions are reproducible, observable, secure, and production‑ready. The mission of this role is to accelerate the operationalization of AI by providing robust MLOps and Dev Ops capabilities that enable reliable, scalable, and maintainable AI services.
Key Duties Design, implement, and maintain CI/CD pipelines for AI and machine learning solutions.
Support deployment, versioning, release management, and rollback processes for AI services.
Implement monitoring, logging,



alerting, and observability capabilities for AI systems and infrastructure.
Manage model registries, experiment tracking platforms, and deployment metadata.
Automate infrastructure provisioning, configuration management, and operational workflows.
Collaborate with AI engineers, platform teams, security teams, and cloud administrators.
Support environment standardization, reproducibility, and operational best practices.
Define operational procedures, runbooks, and incident response processes.
Support troubleshooting, performance optimization, and continuous improvement of production AI services.
Contribute to MLOps, Dev Ops, and platform engineering standards across the AI Factory. Requirements
Education Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Telecommunications Engineering, Information Systems, or a related technical discipline. Essential Knowledge and Professional Experience 3–5 years of experience in Dev Ops, MLOps, Platform Engineering, Site Reliability Engineering (SRE), or related roles.
Experience designing and operating CI/CD pipelines in production environments.
Experience with containerization technologies such as Docker and orchestration platforms such as Kubernetes.
Knowledge of Infrastructure as Code (Ia C) practices and automation frameworks.
Experience with monitoring, logging, observability, and alerting solutions.
Understanding of machine learning and generative AI deployment lifecycle requirements.
Experience with model registries, experiment tracking tools, and release management processes.
Knowledge of security, access control, environment management, and operational governance.
Strong troubleshooting, automation, and operational problem‑solving skills. Additional Knowledge and Professional Experience Experience supporting LLM, RAG, or Generative AI platforms.
Familiarity with MLflow, Kubeflow, Airflow, Argo CD, or similar MLOps ecosystems.
Experience in HPC, scientific computing, or large‑scale AI infrastructures.
Experience supporting multi‑tenant AI platforms and shared services environments.
Experience working across infrastructure, AI, security, and platform teams.
Adaptability in a fast‑evolving AI and cloud technology environment.
Strong Dev Ops, MLOps, and automation skills.



Competences Ability to build reliable, scalable, and maintainable operational environments.
Strong analytical and troubleshooting capabilities.
Proactive, autonomous, and results‑oriented mindset.
Strong focus on reliability, observability, and operational excellence.
Commitment to continuous improvement and automation. Conditions The position will be located at BSC within the Directors Department
We offer a full‑time contract (35h/week), a good working environment, a highly stimulating environment with state‑of‑the‑art infrastructure, versátil 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: 16/07/2026 Development of the recruitment process 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 [email protected].
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📌 Ai Factory Engineer - Devops/mlops (Barcelona)
🏢 Barcelona Supercomputing Center
📍 Barcelona