At a Glance
- Tasks: Design and deliver impactful machine learning models to transform train travel.
- Company: Join Trainline, a leader in sustainable travel technology.
- Benefits: Enjoy private health insurance, work-from-abroad options, and generous learning budgets.
- Other info: Collaborative environment with a focus on career growth and diversity.
- Why this job: Shape the future of travel with cutting-edge AI and ML solutions.
- Qualifications: Advanced degree in a quantitative field and proficiency in Python required.
The predicted salary is between 60000 - 80000 € per year.
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.
Machine learning and 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 recommendation 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
About the role
We are looking for Machine Learning Engineers to join our team to 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.
Key responsibilities
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 enable the acceleration of our ML & AI product delivery and improve our workflows.
Take an active part in our AI and ML community and foster a culture of rigorous learning and experimentation.
What we’re looking for
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).
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 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 broad 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, retrieval‑augmented generation, agents).
Experience with graph technology and/or algorithms.
Benefits and working conditions
We offer private health and dental insurance, a generous work‑from‑abroad policy, 2‑for‑1 share purchase plans, an EV scheme, extra festive time off, and family‑friendly benefits.
We prioritise career growth with clear career paths, transparent pay bands, personal learning budgets and regular learning days. We operate a hybrid model, asking that Trainliners work from the office a minimum of 60 % of the time over a 12‑week period, and we also have a 28‑day work‑from‑abroad policy.
Equal Opportunity Employer
We know that having a diverse team makes us better and helps us succeed. We are committed to creating inclusive places to work, where everyone belongs and differences are valued and celebrated.
Machine Learning Engineer in London employer: Trainline plc
At Trainline, we are dedicated to fostering a culture of innovation and sustainability, making us an exceptional employer for Machine Learning Engineers. Our commitment to employee growth is evident through clear career paths, personal learning budgets, and a collaborative environment where you can work alongside passionate professionals on impactful projects. With generous benefits including private health insurance, a flexible work-from-abroad policy, and a focus on diversity and inclusion, Trainline offers a rewarding workplace that empowers you to shape the future of travel.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Trainline on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can make you stand out in interviews.
✨Tip Number 3
Practice makes perfect! Brush up on common ML interview questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills and get comfortable with the types of problems you might face.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in being part of the Trainline team.
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Show Your Passion for Machine Learning:When you're writing your application, let your enthusiasm for machine learning shine through! We want to see how your love for the field aligns with our mission to create impactful solutions for sustainable travel.
Tailor Your Experience:Make sure to highlight your relevant experience in machine learning and AI. We’re looking for specific examples of projects or models you've worked on that demonstrate your skills and how they can benefit Trainline.
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and fit for the role. Avoid jargon unless it's necessary!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Trainline plc
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially those mentioned in the job description. Be ready to discuss your experience with Python and libraries like Pandas and Scikit-learn, as well as any projects where you've productionised ML models.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles and how you tackled them. Use examples that highlight your ability to work with cross-functional teams and deliver impactful solutions, just like Trainline aims to do.
✨Get Familiar with Their Tech Stack
Since Trainline uses tools like Spark and DevOps technologies such as Docker and Terraform, it’s a good idea to have a basic understanding of these. If you’ve worked with ML Ops platforms like ML Flow, be sure to mention that too!
✨Communicate Clearly
Great communication skills are key for this role. Practice explaining complex technical concepts in simple terms, as you'll need to collaborate with various stakeholders. Being able to convey your ideas clearly will set you apart from other candidates.
