MLOps Engineer Senior

📋 Description

• Industrialize, deploy, and scale Machine Learning models into production environments.
• Design and maintain training, inference, and retraining pipelines end-to-end.
• Build and maintain CI/CD pipelines for ML workflows, ensuring smooth and reliable releases.
• Develop and expose APIs for model serving, ensuring performance and scalability.
• Orchestrate workflows and jobs on Databricks (Workflows, Jobs, Repos).
• Containerize ML applications with Docker and support deployment on Kubernetes-based infrastructure.

🎯 Requirements

• Advanced Python and SQL.
• Experience with Spark / PySpark.
• Solid experience with CI/CD pipelines and Git.
• Experience with MLflow (tracking, registry, and deployment).
• Experience with Docker and working knowledge of Kubernetes concepts.
• Experience with Azure Cloud.

🎁 Benefits

• Remote-first culture – work from anywhere!
• In-Company English Lessons.
• Wellhub or sports club stipend to stay active
• AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
• Food credits via Pedidos Ya – because great work deserves great food.
• Birthday off + an extra vacation week (Mutt Week!)