Job - ML Ops Engineer | MBN
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ML Ops Engineer

  • Data Science
  • Edinburgh
  • Permanent
  • £70,001-£80,000
  • About the role


    ML Ops Engineer – Climate Change (Fully Remote)

    £60,000 - £80,000 + Extensive Bonus & Benefits

    MBN are partnering exclusively with a global business to help them scale their new climate change business unit. This team has been set up to understand how Climate change will impact people and businesses across the UK and use research, statistics and machine learning to help mitigate risk through the creation of new products and services in collaboration with one of the world’s leading Tech companies.

    About the role:

    • You’ll play a vital role in helping the business to make climate-first business decisions, quantifying the environmental impact of customers to reduce their carbon footprint in an economically sustainable manner.
    • You’ll support migration of a number of different ML algorithms to a new Kepler platform and support deployment activities.
    • You’ll work alongside a Climate Data Science team (1st of its kind within the business) and support their programming, testing and deployment of ML models.
    • You will promoting excellence across the lifecycle of Model Validation & Risk, Monitoring & Retraining, Technical Assurance, CICD and adoption of new techniques

    The skills you'll need

    • Experience developing ML Pipelines with modular components such as versioning, tracking and reporting
    • Solid understanding of Software Engineering principles with a particular focus on CI/CD implementation
    • Full stack deployment experience ideally through a cloud platform such as AWS Sagemaker or through containerised methods such as Kubernetes and Docker
    • Experience of Data Engineering excellence particularly in regard to python, spark and pipeline development
    • Develops tests (unit tests, integration tests, non-functional tests, regression tests) for ML pipelines
    • Build ML Pipelines and model monitoring solutions
    • Orchestration for successful management of ML applications
    • Builds capabilities to improve speed/efficiency of deployed models
    • Support on how to package and test the algorithm whilst being aware of the business risk
    • Ops – technical skills around model monitoring & control


    Additional Benefits

    Flexible/Remote working environments (9 day fornights, 4 day weeks etc, accommodating working hours)

    Expectation for the role to be office based 1 or 2 times a month. Offices held in Edinburgh, London, Birmingham, Manchester or Bristol

    For more information or to apply, please send across your updated CV to or apply now.