At a Glance
- Tasks: Join a team of experts to design and deliver impactful machine learning solutions for sustainable travel.
- Company: Trainline, Europe's leading independent rail platform focused on greener travel choices.
- Benefits: Enjoy private healthcare, generous work-from-abroad policy, and excellent career growth opportunities.
- Other info: Collaborative environment with a strong focus on diversity and personal development.
- Why this job: Shape the future of travel with cutting-edge AI and ML technologies that make a real difference.
- Qualifications: Advanced degree in a quantitative field and proficiency in Python and machine learning.
The predicted salary is between 63000 - 77000 £ per year.
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.
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 AIData-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.
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-endmachine 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.
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 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 with graph technology and/or algorithms 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.
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.
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.
Machine Learning Engineer*in in London employer: Trainline
Trainline is an exceptional employer, dedicated to fostering a culture of innovation and sustainability in the travel industry. With a strong emphasis on employee growth, we offer clear career paths, personal learning budgets, and a supportive environment for mentorship and collaboration. Our hybrid work model, generous benefits, and commitment to diversity make Trainline a rewarding place to build a meaningful career while contributing to a greener future.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer*in in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Trainline or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Trainline.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Trainline.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Trainline that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Machine Learning Engineer*in in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Trainline.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Trainline and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Trainline
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Trainline uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
