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Machine Learning Engineer

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Trainline plc
Full Time position
Listed on 2026-07-14
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 70000 - 100000 GBP Yearly GBP 70000.00 100000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

About us

We are champions of rail, inspired to build a greener, more sustainable 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.

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 Pandas, Numpy, Scikit learn etc.)
  • Have experience product ionising 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 Dev Ops technologies such as Docker and Terraform and ML Ops practices and platforms like ML Flow
  • Have experience with agile delivery methodologies and CI/CD processes and tools
  • Have a broad of understanding of data extraction, data manipulation and feature engineering techniques
  • Are familiar with statistical methodologies
  • Have great communication skills
Nice to have:
  • Experience with transport industry and/or geographical information systems (GIS)
  • Experience with cloud infrastructure
  • Experience with Large Language Models (fine tuning, RAG, agents)
  • Experience…
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