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# Cloud Engineer ( Data Science) | Proximus Ada

- **Company:** Editx Bv
- **Location:** Schaarbeek, Belgium
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing Security, Cloud Engineering, Continuous Delivery, Continuous Integration, Information Engineering, Data Systems, DevOps, Python (Programming Language), Machine Learning, Cloud Services, Infrastructure as Code (IaC), Kubernetes, Information Technology, Bicep, Machine Learning Operations, Docker
- **Published:** September 1, 2026
- **Apply:** https://europa.eu/eures/portal/jv-se/jv-details/NGY5ZGM3YWQtYmQ2ZS00MmMyLTkyZjItMGJhZDA3YTg1OGE4IDM?lang=en

## About the Role

* Master's degree in computer science, data science, engineering, or related field.
 * At least 2 years of experience in data engineering, data science, or related roles.
 * Proficient in Python.
 * Hands-on experience with Azure cloud services, including IaC (Bicep), CI/CD, and cloud security.
 * Knowledge on containerized deployment of ML products - e.g. docker, podman, Kubernetes
 * Excellent communication, collaboration, and problem-solving skills.
 * Fluent in English. Dutch and/or French is considered as a plus.

## Description

We are seeking a Cloud Engineer with a strong background in DevOps, MLOps, and cloud architecture (Azure) to join our team. You will play a pivotal role in designing, deploying, and scaling cloud-based AI and data solutions, leveraging Infrastructure as Code (IaC) and modern DevOps practices. Your expertise will help us deliver robust platforms and services for a wide range of client projects, ensuring security, scalability, and operational excellence., * Architect and design cloud solutions and platforms (Azure), translating business needs into scalable, secure, and cost-effective architectures.

 * Automating everything related to the ML lifecycle to ensure efficiency and scalability.
 * Using Infrastructure as Code (IaC) practices, such as Bicep, to manage and provision resources through code.
 * Implementing best practices for continuous integration and delivery (CI/CD) pipelines, ensuring that ML models are reliably deployed to production environments.
 * Collaborate with data scientists, AI engineers, and business stakeholders to define requirements, select technologies, and deliver end-to-end solutions.
 * Challenge our existing security and reinforce our defenses


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