MLOps Engineer (M/F)

As an MLOps Engineer, you will: Participate in the industrialization of machine learning models in production Design and develop robust data and model pipelines Automate CI/CD workflows for ML projects Deploy, monitor, and maintain scalable models on cloud or on-premise environments Collaborate closely with Data Scientists, Data Engineers, and the DevOps team Ensure versioning, traceability, and governance of data and models Guarantee the quality, security, and performance of solutions put into production

Your daily routine may include the following technologies (indicative):

Languages: Python

Pipeline & orchestration: Airflow, Kubeflow, Prefect or equivalents

CI/CD: GitLab CI, GitHub Actions, Jenkins

Containers & Orchestration: Docker, Kubernetes

Cloud: AWS / GCP / Azure

Models & tracking: MLflow, DVC, Seldon, Feast (Feature Store)

Monitoring & alerting: Prometheus, Grafana, other MLOps tools Master's degree in computer science/AI/engineering or equivalent experience

3+ years of experience in software engineering, DevOps & MLOps

Proficiency in AWS

Hands-on experience with ML pipelines, model production, and containerized services

Best practices in testing, automation, and software quality

Autonomy, service-oriented mindset, and team spirit

Fluent technical English