Machine Learning Engineer

ML Engineer required for a long-term engagement offering competitive rates. This is a hybrid role requiring 2 days onsite per week in West London, working closely with multidisciplinary engineering, data and product teams to develop and deploy machine learning solutions focused on user personalisation, recommendations and content analysis. Key Responsibilities

• Design, develop, train and optimise machine learning models focused on user personalisation
• Develop recommendation engines, ranking algorithms, user segmentation and content analysis solutions
• Build and maintain robust, scalable data pipelines to support feature engineering and model training
• Work with large-scale structured and unstructured datasets
• Deploy, monitor and maintain machine learning models in production environments
• Ensure models deliver high availability, performance and continued relevance
• Design, execute and analyse A/B tests and offline experiments to evaluate model performance
• Use experimentation and data-driven insights to continuously improve ML solutions
• Collaborate with multidisciplinary teams to align machine learning initiatives with business objectives and user needs
• Monitor model performance and identify opportunities for optimisation and improvement
• Evaluate emerging research and developments across machine learning, deep learning and personalisation
• Assess new technologies and approaches for potential integration into existing ML systems Skills & Experience
• Strong commercial experience as a Machine Learning Engineer or in a closely related role
• Strong experience developing and optimising machine learning models
• Experience with personalisation, recommendation systems, ranking algorithms and/or user segmentation
• Strong data engineering and data pipeline development experience
• Experience working with large-scale structured and unstructured datasets
• Proven experience deploying and monitoring ML models in production environments
• Strong understanding of experimentation, A/B testing and offline model evaluation
• Experience working collaboratively across engineering, data, product and business teams
• Strong understanding of machine learning and deep learning research and industry developments
• Ability to translate business and user requirements into practical machine learning solutions
• Experience working in large-scale, production-focused technology environments