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.

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 is at the heart of Trainline's mission to help millions of people make sustainable travel choices every day. Our ML models power critical aspects of our platform, including:

• AI agents improving customer support

• 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 generative AI

• Data-driven digital marketing systems

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.

We are looking for a Machine Learning Engineering Manager to join our team help shape the future of train travel. You will be part of a highly innovative AI and ML platform working alongside engineers, scientists and product managers to tackle complex challenges 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 enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users.

As a Machine Learning Engineering Manager at Trainline you will...

• Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers

• Ensure delivery of high-quality machine learning models and AI Systems at scale that drive measurable impact for our business

• 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

• 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 or a similar quantitative discipline

• Have leadership experience either through previous management or mentorship

• Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.)

• Have experience productionising machine learning models

• Are an expert in at least one of one of: predictive modelling, classification, regression, optimisation or recommendation systems

• Have experience with Spark

• Have knowledge of DevOps 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 good communication skills

Nice to have

• Experience with transport industry and/or geographical information systems (GIS)

• Experience with cloud infrastructure

• Understanding of NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents)

• Experience with graph technology and/or algorithms

Our technology stack

• Python and associated ML/DS libraries (scikit-learn, numpy, LightlGBM, Pandas, LangChain/LangGraph, , TensorFlow, etc...)

• PySpark

• AWS cloud infrastructure: EMR, ECS, Athena, etc.

• MLOps: Terraform, Docker, Airflow, MLFlow

More information:

Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, an EV Scheme to further reduce carbon emissions, extra festive time off, and excellent family-friendly benefits.

We prioritise career growth with clear career paths, transparent pay bands, personal learning budgets, and regular learning days. Jump on board and supercharge your career from day one!

We're operating a hybrid model and ask that Trainliners work from the office a minimum of 60% of their time over a 12-week period. We also have a 28-day Work from Abroad policy.

Our values represent the things that matter most to us and what we live and breathe everyday, in everything we do:

• Think Big - We're building the future of rail

• Own It - We focus on every customer, partner and journey

• Travel Together - We're one team

• Do Good - We make a positive impact

We know that having a diverse team makes us better and helps us succeed. And we mean all forms of diversity - gender, ethnicity, sexuality, disability, nationality and diversity of thought. That's why we're committed to creating inclusive places to work, where everyone belongs and differences are valued and celebrated.

Interested in finding out more about what it's like to work at Trainline? Why not check us out on LinkedIn, Instagram and Glassdoor!