Lead of MLOps

We are hiring! Lead of MLOps

Passionate about AI/ML operations engineering? Join the Data & AI team as Lead of MLOps, where you will lead the construction of robust platforms and intelligent pipelines that enable advanced analytics and model deployment at scale.

Role Objective:

You will be responsible for the complete operation of machine learning models in production: from implementation, hyperparameter tuning, performance monitoring, to automation of workflows on Spark datalake (CEFEO). You will work in close collaboration with data science, product, architecture, and technology teams.

️ Key Responsibilities:

• Implement infrastructure on AWS (Sagemaker Notebooks) for CI/CD of models.
• Develop data and feature pipelines for training and inference.
• Automate processes with PySpark and orchestrators like Airflow or Step Functions.
• Monitor models with Prometheus, Grafana, and custom dashboards.
• Integrate CI/CD workflows with tools like GitHub Actions, Sonarqube, and Nexus.
• Ensure versioning with DVC or MLflow.
• Design scalable and secure solutions under standards like GDPR/CCPA.

Requirements:

• +6 years in design and maintenance of ML pipelines.
• +5 years in cloud platforms (AWS, GCP, Azure).
• +3 years in containerization (Docker, Kubernetes) and model monitoring.
• Experience in IaC (Terraform, CloudFormation) and security in ML workflows.
• Effective collaboration with multidisciplinary teams.

Education:

• Bachelor's degree in Computer Science, Systems, Actuarial Science, or related field.
• Desirable: Master's degree in data science or engineering.
• Plus: Experience in generative AI and LLMs.

Interaction:

You will collaborate with internal teams from Product, Risk, AML (Anti-Money Laundering), CX (Customer Experience), and Operations, as well as maintain contact with technology providers and external consultants.