Qualifications5+ years of experience in Dev Ops, Cloud Engineering, or ML Engineering
3+ years of hands‐on experience in MLOps or operationalizing ML models in production environments
Key ResponsibilitiesArchitect and implement scalable end-to-end ML pipelines (training, validation, deployment, monitoring)
Design and maintain CI/CD pipelines for ML workflows using Azure Dev Ops
Implement automated model versioning, artifact management, and rollback strategies
Provision and manage infrastructure using Infrastructure as Code (Terraform, ARM)
Deploy containerized ML services using Docker and Kubernetes
Implement monitoring frameworks for model performance, drift detection, and data quality
Optimize inference performance, scalability, and cost efficiency
Ensure compliance, governance, and security best practices in cloud ML environments
Provide technical leadership and mentorship to junior engineers
Collaborate closely with Data Science and Engineering teams to define production standards
Required Skills

📌 Mlops Azure Devops Engineer (Heroica Puebla de Zaragoza)
🏢 Apex Systems
📍 Heroica Puebla de Zaragoza