Machine Learning Engineer

Machine Learning Engineer

We're looking for a Machine Learning Engineer to join a growing data team and help build out machine learning capability across a large digital platform. This role is ideal for someone early in their career who enjoys working close to data pipelines, platforms and models - and wants to grow their engineering foundations alongside data science skills.

You'll be working hands-on with machine learning models, data platforms and emerging AI technologies, supporting real-world use cases that impact customers and the business.

What you'll be doing

• Contributing to the development and improvement of machine learning models and analytical assets
• Supporting the build and refinement of data pipelines, features and modelling frameworks
• Working with Python and SQL across modern cloud-based data platforms
• Assist with implementation of LLMs and Generative AI user cases across the business
• Analysing customer behaviour and engagement data to support product, marketing and retention initiatives
• Translating business problems into practical data and modelling solutions
• Collaborating with engineers, data scientists and non-technical stakeholders
• Communicating insights and outcomes clearly to a range of audiences

What we're looking for

• Around 3 - 5 year's experience in a Data Scientist, Machine Learning or data-focused role
• Strong coding experience in Python, SQL and Javascript
• Exposure to machine learning model development
• A solid understanding of data engineering concepts (pipelines, data quality, feature creation)
• Familiarity with cloud computing fundamentals
• Curious, practical mindset - comfortable getting hands-on and learning as you go
• Able to explain technical concepts clearly and work collaboratively across teams

Nice to have

• Experience with Snowflake or similar cloud data platforms
• Exposure to Dataiku or other data science platforms
• Experience with modern ML libraries (e.g. scikit-learn, TensorFlow, PyTorch)
• Understanding of model deployment, monitoring or MLOps concepts
• Background in financial services, insurance or member-based organisations
  

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