Head of Machine Learning Engineering
Trainline · London
About this role
About us We are champions of rail, inspired to build a greener, more sustainable https://www.thetrainline.com/terms/sustainability-faqs future of travel. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through our highly rated mobile app, website, and B2B partner channels. Great journeys start with Trainline 🚄 Now Europe’s number 1 downloaded rail app, with over 135 million monthly visits and £6.3 billion in annual ticket sales, we collaborate with 270+ rail and coach companies in over 40 countries. We want to create a world where travel is as simple, seamless, eco-friendly and affordable as it should be. Today, we're a FTSE 250 company driven by our incredible team of over 1,000 Trainliners from 50+ nationalities, based across London, Paris, Barcelona, Milan, Edinburgh and Madrid. With our focus on growth in the UK and Europe, now is the perfect time to join us on this high-speed journey. Introducing Machine Learning and AI at Trainline 👋 Machine learning and AI are central to how Trainline helps millions of customers make smarter, more sustainable travel choices every day. Our ML models and AI systems power critical parts of the platform - from search and recommendations to pricing intelligence, personalisation, digital marketing, and AI-driven customer support. Our ML teams own the full delivery lifecycle, from ideation through to production. We work closely with stakeholders across the business to expand the reach and impact of ML and AI throughout Trainline. The Role This is a senior leadership role sitting within one of Trainline’s most important product areas: Core Experience. This pillar encompasses the products and systems closest to the customer journey - search, pricing, payments, fare intelligence, and conversational interfaces. You will define and lead the ML strategy, team, and delivery across this domain. That means building and scaling ML and AI capabilities that measurabl
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