Machine Learning Engineer

Reed
Bristol
4 months ago
Applications closed

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Machine Learning Engineer / MLOps Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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

You’ll 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 You’ll 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.

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