Machine Learning Engineer Expert

About the role

AXA is looking for an experienced Machine Learning Engineer to design, develop, deploy and optimise large-scale AI models that meet business needs. The role plays a key part in building a robust, scalable MLOps architecture so that production solutions run reliably and efficiently on the Azure cloud.

Key responsibilities

• Design, train and optimise machine learning and deep learning models with TensorFlow, PyTorch and Scikit-learn, working with data scientists to turn prototypes into production solutions.
• Set up CI/CD pipelines for training, evaluation and deployment on Azure, automating them for continuous, reliable delivery.
• Improve inference performance, reduce latency and optimise costs, adjusting models for scalability and robustness.
• Help build an MLOps architecture covering data and model versioning, model registry, monitoring and incident management.
• Document models, pipelines and processes to ensure maintainability, reusability and compliance with company standards.
• Work closely with Data Science, Data Engineering and DevOps teams in an agile, multicultural environment.

Required profile

• At least 5 years in machine learning, data engineering or related fields.
• Proven experience delivering end-to-end model deployment, monitoring and maintenance in production.
• Cloud experience, preferably with Azure, for implementing MLOps solutions.
• Analytical mindset, excellent communication and collaboration skills, and ability to own projects in agile, multicultural settings.

Required skills

• Python, SQL, PySpark
• TensorFlow, PyTorch, Scikit-learn, MLflow, Kubeflow
• Azure (Azure ML, AKS, Data Lake, Data Factory, Databricks)
• Docker, GitHub Actions, Azure DevOps; Terraform preferred
• Understanding of distributed systems, data and model versioning and scalable deployment