Responsibilities
- Define the strategic direction, long-term vision, and roadmap for machine learning within the Core Experience domain, while managing the full budget for cloud resources, tools, and vendor expenses.
- Lead and develop engineering teams through people managers and technical leads, shaping hiring plans and cultivating a culture focused on technical rigor, experimentation, and consistent delivery.
- Collaborate with product, engineering, and business units to uncover high-impact use cases and expand the adoption of machine learning across the organization.
- Oversee end-to-end delivery of ML-powered features in search ranking, payment modeling, fare optimization, supply automation, and conversational AI, ensuring robust deployment and monitoring practices.
- Establish strong operational standards for ML systems, including service level indicators, incident response, and on-call protocols to improve reliability in production environments.
- Co-define the operating framework for modern AI capabilities, including large language models, agent-based architectures, evaluation methodologies, and safety controls.
- Advance governance practices around AI, focusing on data privacy, security compliance, auditability, and ethical deployment as systems scale.
- Ensure sustainable investment balance between immediate deliverables and foundational platform development.
Work Arrangement
Hybrid — London, Paris, Barcelona, Milan, Edinburgh, Madrid
Other
- Access to private healthcare and dental insurance benefits
- Generous work-from-abroad allowance
- 2-for-1 employee share purchase opportunity
- Electric vehicle scheme supporting sustainability goals
- Additional holiday time during festive periods
- Comprehensive family-friendly policies and support
- Clear career progression paths with transparent pay bands and individual learning budgets
- Hybrid working model requiring minimum 60% office presence over a 12-week cycle
- 28-day work-from-abroad policy available annually