Analista de MLOps Sênior

At Nava, we believe in the power of technology to transform businesses — and we have a challenging and strategic opportunity waiting for you.

Come write code with us! 🚀

You will work on building, automating, maintaining, and evolving the platforms and processes that support the lifecycle of Machine Learning models, ensuring scalability, reliability, and operational efficiency.

Main Responsibilities

• Structure and automate training, deploy, and model monitoring pipelines.
• Develop and maintain CI/CD processes for applications and Machine Learning models.
• Work on integration between Data Science, Data Engineering, and Technology teams.
• Implement best practices for versioning, observability, monitoring, and model governance.
• Ensure stability, performance, and scalability of Machine Learning environments.
• Support data scientists in operationalizing models in production.

Requirements and Knowledge

• Solid experience in Python and SQL.
• Knowledge of engineering best practices.
• Experience with Git and code versioning processes.
• Experience with CI/CD pipelines.
• Knowledge of containers (Docker) and service orchestration.
• Experience with Cloud environments (preferably AWS).
• Knowledge of automation, monitoring, and application observability.
• Ability to diagnose and solve complex problems in a structured way.

Preferred Qualifications

• Previous experience in Data Science or Machine Learning teams.
• Experience with MLOps tools (MLflow, SageMaker, Kubeflow, Airflow or similar).
• Knowledge of model monitoring and Data Drift.
• Experience with Infrastructure as Code (Terraform, CloudFormation or similar).

Soft Skills

• Strong sense of ownership and autonomy.
• Good communication skills with technical and non-technical audiences.
• Collaborative profile and problem-solving oriented.
• Proactivity in identifying opportunities for improvement and automation.
• Ease in working in multidisciplinary environments.

Interested? Apply for the position and take your technical interview with SophIA:

https://

Code: NAVA-MLOPS