Machine Learning Engineer
Expired
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Hydrogen Group
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Full Time / Permanent
$95,000 - $115,000 per yr
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Posted 7 months ago
This role is expired
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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