Machine Learning Engineer leading churn prediction model development for Architech. Collaborating with teams to optimize customer retention strategies and utilizing advanced AI and data analysis.
About the role
- Machine Learning Engineer developing machine learning systems to enhance travel experience at Trainline. Collaborating in cross-functional teams to tackle complex real-world problems with data.
Responsibilities
- Work in cross-functional teams combining data scientists, software, data engineers, machine learning engineers, and product managers
- Design and deliver scalable machine learning systems that drive impactful, real-world applications
- Work with complex and large-scale datasets to solve challenging business and customer problems
- Contribute to innovative products and features that enhance the travel experience for millions of users
- Own the full end-to-end machine learning delivery lifecycle, including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployment and maintenance
- Partner with stakeholders to propose and develop data-driven solutions leveraging Trainline’s rich datasets and advanced algorithms
- Create tools, frameworks and libraries that accelerate ML product delivery and improve team workflows
- Take an active part in our AI and ML community and foster a culture of rigorous learning and experimentation
Requirements
- Strong understanding of machine learning fundamentals and core modelling techniques
- Proficient in Python and common ML/data libraries (e.g. Pandas, Numpy, Scikit-learn)
- Experience with large-scale data processing frameworks such as Spark
- Experience building and productionising machine learning models, including real-time systems, with knowledge of MLOps, APIs and CI/CD practices
- Strong communication skills and comfortable presenting complex ideas to non-technical audiences
- Experience or interest in geospatial data, graph-based methods or network modelling (highly desirable)
- Experience in relevant industry such as travel, mobility or transport, or related industries such as logistics, aviation or supply chain (highly desirable)
Benefits
- Private healthcare & dental insurance
- Generous work from abroad policy
- 2-for-1 share purchase plans
- EV Scheme to further reduce carbon emissions
- Extra festive time off
- Excellent family-friendly benefits
- Clear career paths
- Transparent pay bands
- Personal learning budgets
- Regular learning days
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