Overview
About Trainline 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. We are Europe’s number 1 downloaded rail app, with over 125 million monthly visits and £5.9 billion in annual ticket sales, collaborating with 270+ rail and coach companies in over 40 countries. We strive for travel that is simple, seamless, eco-friendly and affordable. We are a FTSE 250 company with a diverse team of over 1,000 Trainliners from 50+ nationalities, based across London, Paris, Barcelona, Milan, Edinburgh and Madrid. We value learning and development and offer opportunities to grow in a high-speed journey.
Role
We are looking for a Machine Learning Engineering Manager to join our team and shape the future of train travel. You will be part of a highly innovative AI and ML platform working alongside engineers, scientists and product managers to tackle complex challenges by combining Trainline’s rich datasets with cutting edge algorithms. The team is united by expertise, passion, and a drive to create impactful solutions that support Trainline’s goals of encouraging sustainable travel. You will join an environment where learning and development is a top priority, work with fellow ML enthusiasts on large-scale production systems, and deliver products that make a difference to millions of users.
Responsibilities
- Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers
- Ensure delivery of high-quality machine learning models and AI systems at scale that drive measurable impact for the business
- 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
- Take an active part in the AI and ML community and foster a culture of rigorous learning and experimentation
Requirements
- Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline
- Have leadership experience either through previous management or mentorship
- Are proficient with Python, including open-source data libraries (e.g., Pandas, NumPy, Scikit-Learn)
- Have experience productionising machine learning models
- Are an expert in at least one of: predictive modelling, 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 MLflow
- 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 transport industry and/or geographical information systems (GIS)
- Experience with cloud infrastructure
- Understanding of NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents)
- Experience with graph technology and/or algorithms
Technology stack
- Python and associated ML/DS libraries (scikit-learn, numpy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc.)
- PySpark
- AWS cloud infrastructure: EMR, ECS, Athena, etc.
- MLOps: Terraform, Docker, Airflow, MLFlow
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 operate a hybrid model requiring Trainliners to 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.
Values
- Think Big - We're building the future of rail
- ✔️ Own It - We focus on every customer, partner and journey
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