Junior Machine Learning Engineer

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 across our mobile and web applications, pricing and routing optimisation, personalised experiences enhanced by agentic AI, data-driven marketing systems, and AI agents that improve customer support. Our machine learning teams own the complete delivery lifecycle from ideation to production, working closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline., We are looking for a Junior Machine Learning Engineer to join a high-performing, deeply technical community of Machine Learning Engineers, Data Scientists and Data Engineers who tackle complex problems by combining Trainline’s rich datasets with cutting-edge algorithms. You will be supported to grow your skills through hands-on project work, close collaboration with more experienced colleagues, and a genuine culture of learning and development, while contributing to large-scale production systems that make a real difference to millions of customers.

In this role as the Junior Machine Learning Engineer, you will…

• Work within cross-functional teams alongside data scientists, software engineers, data engineers and product managers
• Support the design and delivery of machine learning models and AI solutions that contribute to measurable impact for Trainline
• Get involved across the machine learning delivery lifecycle, including data exploration, feature engineering, model selection and evaluation
• Collaborate with stakeholders to help shape data products that make good use of Trainline’s extensive datasets
• Contribute to the tools, frameworks and libraries that help accelerate our ML and AI delivery and improve our workflows
• Take part in our AI and ML community, sharing learning and building your experimentation skills alongside others

• A good working knowledge of Python, including open-source data libraries such as Pandas, NumPy or Scikit-learn
• A background in Computer Science, Mathematics, Statistics or a similar quantitative discipline, whether through study or practical experience
• Some exposure to building or supporting machine learning models or AI solutions, gained through study, projects or early career experience
• An interest in areas such as predictive modelling, classification, regression, optimisation, NLP or recommendation systems
• A curious, collaborative approach and strong communication skills, with an eagerness to learn from others
• It would be helpful if you have had some exposure to Spark or similar data processing tools
• You may also have some familiarity with DevOps or MLOps tools such as Docker, Terraform or MLflow
• Ideally, you will have an interest in agile ways of working and CI/CD practices, though this is not essential

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.