Machine Learning Engineer

Stack

Responsibilities

• ▹Work in cross-functional teams with data scientists, software, data and machine learning engineers, and product managers
• ▹Design and deliver machine learning models and/or AI solutions at scale with measurable business impact
• ▹Own the end-to-end ML delivery lifecycle: data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployment and maintenance
• ▹Partner with stakeholders to propose innovative data products built on Trainline's datasets and state-of-the-art algorithms
• ▹Build tools, frameworks and libraries that accelerate ML & AI product delivery and improve workflows
• ▹Take an active part in Trainline's AI and ML community, fostering a culture of learning and experimentation

Requirements

• ▹Advanced degree in Computer Science, Mathematics, Statistics or a similar quantitative discipline
• ▹Proficiency with Python, including open-source data libraries such as Pandas, NumPy, Scikit-learn
• ▹Experience productionising machine learning models and/or AI solutions
• ▹Expertise in one of: predictive modelling, classification, regression, optimisation, NLP algorithms or recommendation systems
• ▹Experience with Spark
• ▹Knowledge of DevOps technologies such as Docker and Terraform

About the company

Trainline is Europe's number 1 downloaded rail app, enabling millions of travellers to find and book the best value tickets across carriers, fares and journey options via its mobile app, website and B2B partner channels. The FTSE 250 company partners with over 270 rail and coach companies in more than 40 countries and employs over 1,000 people from 50+ nationalities across offices in London, Paris, Barcelona, Milan, Edinburgh and Madrid.