About this role
Based in London, the Embedded Data Engineer - ML role at Trainline involves creating data pipelines and models to power machine learning applications and analytics. This position suits data professionals with cloud environment experience who want to build infrastructure supporting green travel initiatives.
Role Overview
Trainline seeks an Embedded Data Engineer for their Machine Learning team in London. The position operates under a hybrid model requiring office presence at least sixty percent of the time over a twelve-week period. The professional filling this position will construct data pipelines, models, and feature stores that support analytical and machine learning workloads.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Trainline is Europe's leading independent rail platform connecting travellers with tickets through mobile apps, websites, and B2B partner channels. The company employs over one thousand people across multiple European cities with a mission to encourage greener travel choices and positive environmental impacts.
How to Apply
Candidates should apply directly on the official Trainline careers page.
Skills and tech stack
Questions candidates ask
Where is the Embedded Data Engineer - ML position located?
The role is located in London with a hybrid work model requiring employees to work from the office a minimum of 60% of their time over a 12-week period.
What is the salary range for this job?
The salary range is between £60,000 and £67,500.
What team will the engineer sit within?
The engineer will sit within the Machine Learning team, working alongside Machine Learning Engineers and Data Scientists.
What primary tools and technologies are required?
Required tools and technologies include Python, SQL, Spark, Airflow, and AWS cloud environments.
What perks and benefits does Trainline offer?
Perks include private healthcare and dental insurance, a 28-day work from abroad policy, 2-for-1 share purchase plans, an electric vehicle scheme, extra festive time off, family-friendly benefits, personal learning budgets, and regular learning days.