Machine Learning Engineer
ML Ops Engineer
Remote (Occasional London Meetups) | Full-Time, Permanent | UK Based | Cannot sponsor
Specialising in Azure ML, Data Integration & Scalable ML Ops
Are you an experienced ML Ops Engineer with a passion for deploying scalable machine learning solutions in Azure? This remote-first role (with occasional meetups in London) offers the opportunity to work on impactful data analytics projects in the pensions advisory space.
About the Role
Youll be part of a forward-thinking analytics team that supports over 1,400 pension schemes and delivers insights using advanced technology and data science. We value innovation, collaboration, and continuous learning.
Please note: We are unable to offer visa sponsorship for this role. Applicants must have the right to work in the UK.
Key Responsibilities
- Azure ML Operations : Design, deploy, and manage ML models in production using Azure ML .
- Data Integration : Build and maintain data pipelines using SQL and Azure Data Factory (ADF) .
- ML Ops : Implement CI/CD workflows, monitor model performance, and manage retraining pipelines.
- Python Development : Write clean, scalable code and manage version control using Git .
- Cross-functional Collaboration : Work closely with actuaries, analysts, and developers to translate data science into actionable insights.
- Innovation & Support : Stay current with ML trends and support team learning in tools and techniques.
What Youll Bring
Essential Experience:
- Strong hands-on experience with Azure ML or Azure-based production environments.
- Proficiency in Python , SQL , ADF (Azure Data Factory) , and Git .
- Solid understanding of ML Ops , CI/CD, and model lifecycle management.
- Ability to communicate technical concepts to non-technical stakeholders.
Desirable:
- Experience in pensions or regulated financial services.
- Background in multidisciplinary team environments.
- Company
- Reed
- Location
- Guernsey, UK
Hybrid / WFH Options - Employment Type
- Part-time
- Posted
- Company
- Reed
- Location
- Guernsey, UK
Hybrid / WFH Options - Employment Type
- Part-time
- Posted