About Trainline
Trainline is a FTSE 250 company dedicated to building a greener, more sustainable future of travel through rail. With over 110 million monthly platform visits and £4.3 billion in net ticket sales, we are continually innovating to make travel simple, seamless, and affordable. We are a diverse team of over 1000 Trainliners from 60+ nationalities across multiple European offices.
Introducing Machine Learning at Trainline
Machine Learning is central to Trainline’s mission to help millions of people make sustainable travel choices daily. Our ML models enhance search capabilities, find the cheapest prices, improve user experience with generative AI, and power digital marketing. Our embedded machine learning teams manage the full end-to-end delivery lifecycle from ideation to production, collaborating closely with various business divisions to advance the understanding and impact of ML and AI.
We are seeking a Machine Learning Engineer to join our team, playing a key role in enhancing the experience for millions of customers. This role offers broad exposure, requiring close collaboration with retail, marketing, and technology divisions. You will work within an innovative AI and ML platform alongside data engineers, data scientists, and product managers to solve complex problems using Trainline’s rich datasets and cutting-edge technology. We are united by our expertise, passion, and the desire to create impactful solutions supporting sustainable travel goals.
As part of Trainline, you will receive a competitive salary and benefits, and join an environment where your development is a top priority. You will work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products for millions of users.
As a Machine Learning Engineer at Trainline you will...
- Work in cross-functional teams combining data science, data engineering, BI, machine learning, and product management.
- Implement and deploy machine learning models at scale that drive measurable business impact.
- Partner with stakeholders to propose innovative data products leveraging Trainline’s rich datasets and state-of-the-art ML algorithms.
- 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.
- Create the tools, frameworks, and libraries that accelerate ML product delivery and improve workflows.
- Take an active part in our AI and ML community and foster a culture of rigorous learning and experimentation.
Qualifications
We'd love to hear from you if you...
- Have an advanced degree in Computer Science, Mathematics, or a similar quantitative discipline.
- 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 one of predictive modeling, 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 understanding of data extraction, data manipulation, and feature engineering techniques.
- Are familiar with statistical methodologies.
- Have good communication skills.
Nice to have
- Experience with the transport industry and/or geographical information systems (GIS).
- Experience with cloud infrastructure.
- Understanding of NLP algorithms and techniques.
- Experience with Large Language Models (fine-tuning, RAG, agents).
Our technology stack
- Python
- PySpark for processing big data
- AWS: EMR, ECS, Athena, etc.
- DevOps: Terraform, Docker, Airflow, MLFlow