ML Engineer

As a Machine Learning Engineer, you will design, train, optimise and deploy machine learning models focused on user personalisation, including recommendation engines, ranking algorithms, user segmentation and content analysis.

You will work across the full machine learning lifecycle, from data pipeline engineering and feature development through to production deployment, experimentation and ongoing model optimisation.

Key responsibilities will include:

• Designing, training and optimising machine learning models
• Developing solutions for user personalisation and recommendation
• Building recommendation engines and ranking algorithms
• Developing user segmentation and content analysis models
• Designing and maintaining scalable data pipelines
• Supporting feature engineering and model training using large-scale structured and unstructured datasets
• Deploying and monitoring ML models in production environments
• Ensuring model availability, performance and continued relevance
• Designing and analysing A/B tests and offline experiments
• Using experimentation to evaluate model efficacy and drive continuous improvement
• Working collaboratively with multidisciplinary teams to align ML initiatives with business and user needs
• Evaluating emerging research across machine learning, deep learning and personalisation
• Identifying opportunities to integrate new techniques and research into existing systems

• Strong professional experience in Machine Learning Engineering
• Experience developing and optimising personalisation or recommendation models
• Strong understanding of recommendation systems and ranking algorithms
• Experience with user segmentation and/or content analysis
• Experience building scalable data pipelines
• Strong experience with feature engineering
• Experience working with large-scale structured and unstructured datasets
• Experience deploying and monitoring ML models in production
• Experience with A/B testing and offline experimentation
• Strong understanding of machine learning and deep learning
• Experience working collaboratively with data, engineering, product and other multidisciplinary teams
• Ability to evaluate and apply emerging ML research and techniques