Infrastructure Manager (MLOps)

Join a leading innovator at the intersection of Quantum, AI, and advanced engineering, where cutting-edge research meets real-world impact.

We are seeking an Engineering Manager - R&D Automation who will play a pivotal role in shaping and scaling automation capabilities across next-generation machine learning and research platforms. In this position, you will guide a talented technical team, collaborate with top-tier experts, and drive initiatives that enable seamless experimentation, robust deployment pipelines, and high-performance ML infrastructure.

This is an opportunity to contribute to groundbreaking projects in an environment that values curiosity, responsibility, diversity, and sustainable innovation.

This role is offered as an initial Fixed-Term Contract, with a hybrid working model from offices in Madrid or Barcelona.

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field.
• 3+ years of experience in MLOps or Machine Learning Engineering, or 5+ years in DevOps roles supporting ML systems.
• Ability to translate business goals into MLOps strategy, aligning technical initiatives with product and research needs.
• Strong project management skills, including sprint planning, roadmap creation, and cross-functional coordination.
• Proven ability to build and scale high-performing MLOps teams, fostering collaboration, innovation, and continuous improvement.
• Excellent communication skills for both technical and non-technical stakeholders.
• Strong proficiency with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Helm).
• Proven experience managing CI/CD pipelines for ML workflows using tools such as GitLab CI/CD, Jenkins, or Argo Workflows.
• Expertise in Infrastructure as Code (Terraform or CloudFormation).
• Deep understanding of model deployment, monitoring, and scaling in production environments.
• Hands-on experience with ML workflow orchestration tools (Flyte, Kubeflow, Airflow, MLflow).
• Solid foundation in GitOps principles and model registry management.
• Experience with observability and monitoring tools (Prometheus, Grafana, OpenTelemetry, etc.).