Machine Learning Engineer at Trainline in London

  • Company: Trainline
  • Location: London
  • Job type: full time
  • Workplace: remote
  • Posted: 2026-07-08

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Job description

About us At Trainline, our purpose is to empower greener travel choices, connecting people and places. 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 🚄 We’re Europe’s leading independent rail platform, helping millions of travellers find and book the best-value rail and coach journeys across our app, website and partner channels. Our job is to make the green travel choice the best choice. By building a better train travel experience, we help more people choose rail - creating a positive impact for customers, our business and the planet. We’re a team of more than 1,000 Trainliners from over 50 nationalities, working across London, Paris, Barcelona, Milan, Edinburgh and Madrid. Now is a brilliant time to join us and help shape the future of travel. Introducing Machine Learning & AI at Trainline 👋 Machine learning and AI are at the core of how Trainline is transforming travel, helping millions of customers make smarter, more sustainable journeys every day. Our ML models and AI solutions power critical aspects of our platform, including: • Advanced search and recommendations capabilities across our mobile and web applications • Pricing and routing optimisations to find the best fares for customers • Personalised user experiences enhanced by agentic AI • Data-driven digital marketing systems • AI agents improving customer support Our machine learning teams own the complete delivery lifecycle from ideation to production. We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. About The Role We are looking for Machine Learning Engineers to join our team help shape the future of train travel. You’ll be joining a high-performing, deeply technical community of Machine Learning Engineers, Data Scientists, and Data Engineers to tackle complex problems by combining Trainline’s rich datasets with cutting edge algorithms. What unites our team is an expertise in the field, a love of what we do and the desire to create impactful solutions to support Trainline’s goals of encouraging sustainable travel. As a part of Trainline you will be joining an environment where learning and development is top priority. You will have the opportunity to work with fellow ML & AI enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of customers. As a Machine Learning Engineer at Trainline you will... 🚄 • Work in cross-functional teams combining data scientists, software, data and machine learning engineers, and product managers • Design and deliver machine learning models and/or AI solutions at scale that drive measurable impact for Trainline • Own the full end-to-end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance • Partner with stakeholders to propose innovative data products that leverage Trainline’s extensive datasets and state of the art algorithms • Create the tools, frameworks and libraries that enables the acceleration of our ML & AI products delivery and improve our workflows • Take an active part in our AI and ML community and foster a culture of rigorous learning and experimentation We'd love to hear from you if you...🔍 • Have an advanced degree in Computer Science, Mathematics, Statistics or a similar quantitative discipline • Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) • Have experience productionising machine learning models and/or AI solutions • Are an expert in one of predictive modelling, classification, regression, optimisation, NLP algorithms or recommendation systems • Have experience with Spark • Have knowledge of DevOps

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