Senior MLOps Engineer
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Summary
Senior MLOps Engineer (Madrid, remote-friendly) who builds, automates, and maintains end-to-end ML pipelines and production ML platforms — handling experiment tracking, model registry, deployment, and monitoring with Databricks and MLflow. Requires 5+ years in MLOps/ML engineering, strong Python, CI/CD, and cloud experience.
Senior MLOps Engineer
We are seeking a Senior MLOps Engineer with proven experience in building and scaling machine learning operations in production environments. The ideal candidate must have strong hands-on expertise with Databricks and MLflow, as these are core requirements for the role.
What you will do
- Build, automate, and maintain end-to-end ML pipelines
- Deploy, monitor, and optimize machine learning models in production
- Manage experiment tracking, model registry, and lifecycle workflows using MLflow
- Collaborate with data scientists, data engineers, and software teams to productionize ML solutions
- Improve the reliability, scalability, and governance of ML platforms
What we are looking for
- 5+ years of experience in MLOps, Machine Learning Engineering, or similar roles
- Mandatory hands-on experience with Databricks and MLflow
- Strong Python skills and experience working with cloud-based environments
- Solid understanding of CI/CD, automation, model deployment, and monitoring
- Ability to work cross-functionally and communicate clearly with technical and non-technical stakeholders
Nice to have
- Experience with orchestration and infrastructure tools such as Airflow, Docker, Kubernetes, or Terraform
- Familiarity with AWS, Azure, or GCP
