Machine Learning Ops Engineer

About the role

The role focuses on designing, building and operating machine‑learning solutions for a leading UK consulting and administration business serving pension and insurance clients. You will work closely with actuarial and analytics teams to deliver production‑grade models using Azure Machine Learning Studio.

Key responsibilities

• Develop, deploy and monitor predictive models (longevity, default risk, investment outcomes) in Azure Machine Learning Studio.
• Implement MLOps practices: model drift detection, data quality monitoring, automated retraining pipelines and version control.
• Build and maintain scalable data pipelines with Python, SQL and Azure Data Factory.
• Write clean, production‑ready Python code and apply CI/CD and DevOps principles.
• Collaborate with actuarial analysts to translate model outputs into business insights.
• Stay current with Azure ML, MLOps and data‑science advancements, proposing improvements.
• Provide training and knowledge‑sharing on Azure ML workflows and monitoring.
• Communicate technical concepts clearly to both technical and non‑technical stakeholders.

Required profile

• Strong hands‑on experience with Azure Machine Learning Studio, from model development to deployment.
• Proven ability to manage the full ML lifecycle in a production environment.
• Experience working with cross‑functional teams, especially actuarial or analytics groups.
• Excellent communication skills for explaining complex ML concepts.

Required skills

• Azure Machine Learning Studio
• Azure Data Factory
• Python
• SQL
• CI/CD pipelines
• DevOps / MLOps practices
• Version control (e.g., Git)
• Model monitoring and drift detection

What we offer

• Remote working within the UK
• Salary range £45,000–£60,000 per year plus a 6% performance bonus