Sr Machine Learning Engineer | Rabat (Morocco)

AXA GBS Morocco operates within a predominantly collaborative culture, where people, trust, and strong professional relationships are key priorities. The company promotes close and supportive management, encouraging accountability, development, and team cohesion. This human-centered approach is reinforced by a strong organizational framework, ensuring reliability, structure, and operational efficiency. It is complemented by a moderate focus on innovation and performance, supporting continuous improvement within a well-defined environment.

Model Design and Development:

• Design, train, and optimize Machine Learning and Deep Learning models using frameworks such as TensorFlow, PyTorch, and Scikit-learn. Collaborate with Data Scientists to turn prototypes into production-ready solutions.

Industrialization and Deployment:

• Implement CI/CD pipelines for training, evaluation, and deployment of models on Azure. Automate these processes to ensure continuous, reliable delivery.

Performance Optimization in Production:

• Improve model inference performance, reduce latency, and optimize costs. Make adjustments to ensure scalability and robustness.

MLOps and Cloud Architecture:

• Contribute to building a comprehensive MLOps architecture, including versioning data and models, model registry, monitoring, and incident management.

Documentation and Best Practices:

• Document models, pipelines, and processes to ensure maintainability, reusability, and compliance with company standards.

Collaboration and Communication:

• Work closely with Data Science, Data Engineering, and DevOps teams in an agile, multicultural environment to deliver high-value solutions.

• Minimum of 5 years in Machine Learning, Data Engineering, or related fields
• Proven experience in end-to-end model deployment, monitoring, and maintenance in production
• Cloud experience, ideally with Azure, for implementing MLOps solutions

Technical Skills Required:

• Programming Languages: Python, SQL, PySpark
• ML Frameworks and Tools: TensorFlow, PyTorch, Scikit-learn, MLflow, Kubeflow
• Cloud Platforms: Azure (Azure ML, AKS, Data Lake, Data Factory, Databricks)
• DevOps & Automation: Docker, GitHub Actions, Azure DevOps, Terraform (preferred)
• Distributed Architecture: Strong understanding of distributed systems, data/model versioning, and scalable deployment practices

Soft Skills:

• Analytical mindset with strong technical rigor
• Excellent communication and collaboration skills
• Ability to work in agile, multicultural environments, taking ownership of projects
• Delivery-oriented with a focus on ownership and results