Lead 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.
- Demonstrated expertise in the full lifecycle of machine learning, from model development and deployment to monitoring and maintenance.
- Advanced 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.
- Exceptional communication and analytical problem-solving skills.
- Proven successful experience in mentoring less experienced engineers to improve their technical skills
- Sky Q, for the TV you love all in one place
- The magic of Sky Glass at an exclusive rate
- A generous pension package
- Private healthcare
- Discounted mobile and broadband
- A wide range of Sky VIP rewards and experiences
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