Machine Learning Engineer – Azure & Recommendation Systems

About the role

We are looking for a Machine Learning Engineer to design, build and deploy advanced ML models in a production environment. You will focus on recommendation systems and work closely with data scientists, engineers and product teams to turn business needs into scalable AI solutions.

Key responsibilities

• Develop and optimise personalised recommendation and ranking algorithms.
• Implement and maintain MLOps pipelines for CI/CD, model versioning, monitoring and automation.
• Deploy models on Azure cloud services, ensuring performance, scalability and reliability.
• Process large‑scale datasets, extract insights and continuously improve model accuracy.
• Monitor model performance in production and trigger retraining as needed.

Required profile

• Proven experience as an ML Engineer delivering production‑ready models.
• Strong background in Azure services (Azure ML, Databricks, Data Factory, Azure DevOps).
• Hands‑on experience with MLOps frameworks and recommendation system techniques.

Required skills

• Python
• TensorFlow
• PyTorch
• Scikit‑learn
• Azure ML, Azure Databricks, Azure Data Factory, Azure DevOps
• MLOps (CI/CD, model versioning, monitoring, automation)
• Recommendation systems (collaborative filtering, content‑based, hybrid)
• Apache Spark

What we offer

• £650 per day (PAYE)
• 6‑month contract with hybrid working
• Opportunity to work on cutting‑edge AI projects in a dynamic tech environment