Machine learning engineer in rail

Machine-learning delivery follows models and AI solutions from exploration and feature engineering through evaluation, deployment and maintenance. You will work with data scientists, engineers and product managers on systems that improve Trainline's customer experience.

Design and deliver machine-learning models or AI solutions at scale that produce a measurable effect for Trainline and its customers. Own the delivery lifecycle, from data exploration and feature engineering through model selection, offline and online evaluation, deployment and maintenance. Work in cross-functional teams with data scientists, software engineers, data engineers, machine-learning engineers and product managers. Partner with stakeholders to propose data products that draw on Trainline's extensive datasets and current algorithms.

Create the tools, frameworks and libraries that speed up delivery of machine-learning and AI products and improve the team's workflows.

You have an advanced degree in computer science, mathematics, statistics or a similar quantitative discipline. You are proficient in Python and open-source data libraries such as pandas, Num Py and scikit-learn. You have productionised machine-learning models or AI solutions. You are an expert in one of predictive modelling, classification, regression, optimisation, natural-language processing or recommendation systems. You have used Spark, and you know Docker, Terraform and MLOps practice such as MLflow, plus agile delivery and continuous integration.

Будет плюсом:
Transport or geographic-information-systems experience, cloud infrastructure, large language models, and graph technology are useful, not required

This full-time London role is hybrid, with at least 60% office attendance over 12 weeks.