Overview
As a Machine Learning Engineer at Trainline, you will shape scalable ML solutions that power search, pricing, and personalised experiences. You join a cross-functional team to deliver end-to-end ML projects in production, influencing customer journeys and revenue optimisation. You’ll work with extensive data and cutting-edge algorithms to drive measurable business impact. This role offers hands-on engineering with a strong emphasis on learning, experimentation, and collaboration.
Pay / Benefits
- private healthcare & dental insurance
- work from abroad policy
- 2-for-1 share purchase plans
- EV scheme to reduce carbon emissions
- extra festive time off
- family-friendly benefits
Responsibilities
- Design and deliver ML models at scale to drive business impact
- Own end-to-end ML delivery lifecycle: data exploration, feature engineering, model selection, evaluation, deployment, maintenance
- Collaborate with data scientists, software engineers, and product managers in cross-functional teams
- Prototype data products leveraging Trainline’s datasets and advanced algorithms
- Create tools and frameworks to accelerate ML delivery and improve workflows
- Engage with the AI/ML community to foster learning and experimentation
Key requirements
- Advanced degree in Computer Science, Mathematics or similar quantitative discipline
- Proficiency in Python and data libraries (Pandas, NumPy, Scikit-learn)
- Experience productionising ML models
- Expertise in predictive modelling, classification, regression, optimisation or recommendation systems
- Experience with Spark
- Knowledge of DevOps tech (Docker, Terraform) and ML Ops platforms (MLflow)
- Experience with agile delivery, CI/CD tools
- Broad understanding of data extraction, manipulation, and feature engineering
- Familiarity with statistical methodologies
- Good communication skills
- strong communication
- collaboration
- curiosity and learning mindset
- Python and open-source data libraries
- Spark
- Docker
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