Machine Learning Engineer

Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

• Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
• Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.
• Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
• Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
• Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
• Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

• Demonstrated expertise in the full lifecycle of machine learning, from model development and deployment to monitoring and maintenance.
• Proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch).
• Experience with high-volume data processing and real-time streaming architectures.
• Strong understanding of recommendation system design and personalisation algorithms.
• Familiarity with Generative AI and its applications in production settings.
• Good communication and analytical problem-solving skills.

• Generous pension package
• Private healthcare
• Discounted mobile and broadband
• A wide range of Sky VIP rewards and experiences

We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky.