At a Glance
- Tasks: Join a team to design and deliver impactful machine learning models for train travel.
- Company: Trainline, a leading tech company transforming sustainable travel.
- Benefits: Private health insurance, work-from-abroad policy, and generous learning budgets.
- Other info: Inclusive workplace valuing diversity and offering clear career growth paths.
- Why this job: Shape the future of travel with cutting-edge AI and ML technologies.
- Qualifications: Advanced degree in a quantitative field and proficiency in Python.
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. Today, we are a FTSE 250 company, with offices in 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 & 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 and work closely with stakeholders across the business to expand the impact of machine learning and AI throughout Trainline.
About The Role
We are looking for Machine Learning Engineers to join our team and help shape the future of train travel. You’ll join 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.
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 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.
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 such as Pandas, Numpy, and 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 a 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 the 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.
Benefits
Enjoy private health and dental insurance, a generous work‑from‑abroad policy, a 2‑for‑1 share purchase plan, an electric vehicle scheme, extra festive time off, and family‑friendly benefits. We prioritize career growth with clear career paths, transparent pay bands, personal learning budgets, and regular learning days. The hybrid model requires staff to work from the office a minimum of 60 % of their time over a 12‑week period and offers a 28‑day work‑from‑abroad policy.
Values
- Think Big – building the future of rail.
- Own It – focusing on every customer, partner and journey.
- Travel Together – working as one team.
- Do Good – making a positive impact.
Trainline is committed to creating inclusive places to work, where everyone belongs and differences are valued and celebrated. We welcome all forms of diversity – gender, ethnicity, sexuality, disability, nationality and diversity of thought.
Machine Learning Engineer employer: Trainline International Limited
Trainline is an exceptional employer, offering a dynamic work environment where innovation meets sustainability in the travel industry. With a strong focus on employee growth, we provide clear career paths, personal learning budgets, and a culture that values diversity and collaboration. Our London office fosters a high-performing community of Machine Learning Engineers, where you can contribute to meaningful projects that shape the future of rail travel while enjoying comprehensive benefits like private health insurance and a generous work-from-abroad policy.
Contact Details:
Trainline International Limited Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Trainline International Limited!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Machine Learning Engineer at Trainline International Limited.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Trainline International Limited.
✨Apply Directly through Our Website
When you find a suitable opening like Machine Learning Engineer at Trainline International Limited, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Trainline International Limited, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Trainline International Limited. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Trainline International Limited
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Trainline International Limited!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
