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# AI/ML Engineer - Production Machine Learning 10925853

- **Company:** ITProposal
- **Location:** Brussel, Belgium
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Continuous Integration, Python (Programming Language), Machine Learning, Azure Machine Learning, Software Engineering, Management of Software Versions, Pandas, Scikit Learn, Deployment Automation, Xgboost, Machine Learning Operations
- **Published:** August 15, 2026
- **Apply:** https://www.careerjet.be/jobad/be11827e70dd060de5698558a5b79e9f73

## About the Role

* 5+ years of hands-on experience with Python and ML libraries: pandas, scikit-learn, xgboost.
 * Proven experience deploying and maintaining AI/ML services in production.
 * Strong understanding of AI/ML application development, testing, serving, monitoring, and troubleshooting.
 * Experience ensuring model reproducibility and interpretability.
 * Knowledge of Azure Machine Learning (Azure ML) and Azure cloud services.
 * Experience monitoring and maintaining ML services post-deployment.
 * Strong problem-solving skills and ability to work independently.
 * Excellent communication skills and ability to explain complex concepts clearly.

Competencies

 * Digital: Microsoft Azure
 * Digital: Azure Machine Learning (ML)

## Description

We are seeking an experienced AI/ML Engineer with a strong track record in deploying, maintaining, and monitoring machine learning models in production environments. This role is hands-on and requires deep practical experience across Python, ML libraries, Azure Machine Learning, and modern MLOps practices.
You will be responsible for packaging, serving, monitoring, and troubleshooting ML services, ensuring reproducibility, interpretability, and operational excellence across the full lifecycle of AI/ML solutions., * Deploy, package, and maintain AI/ML models and services in production environments.

 * Build and manage ML pipelines for training, testing, serving, and monitoring.
 * Ensure ML models are reproducible, interpretable, and aligned with governance standards.
 * Monitor and troubleshoot production ML services, ensuring reliability and performance.
 * Work with Python and ML libraries (pandas, scikit-learn, xgboost) to develop robust model solutions.
 * Collaborate with cross-functional teams to ensure seamless integration of ML services.
 * Apply best practices in MLOps, including versioning, CI/CD, model registry, and automated deployment.
 * Work within Azure Machine Learning and Azure cloud environments to operationalize ML workloads.
 * Maintain high-quality documentation and communicate technical concepts clearly to stakeholders.


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