1 day ago
London, United KingdomEntry Level
Responsibilities
- Design and deliver machine learning models at scale to drive measurable business impact.
- Own the end-to-end machine learning lifecycle, including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployment, and maintenance.
- Collaborate with data scientists, software engineers, data engineers, ML engineers, product managers, and stakeholders on data-driven products.
- Create tools, frameworks, and libraries that accelerate ML product delivery and improve workflows.
- Participate in the AI and ML community and promote rigorous learning and experimentation.
Requirements
- Hold an advanced degree in Computer Science, Mathematics, or a similar quantitative discipline.
- Demonstrate proficiency with Python and open-source data libraries such as Pandas, NumPy, and scikit-learn.
- Have experience productionising machine learning models.
- Have expertise in at least one of predictive modelling, classification, regression, optimisation, or recommendation systems.
- Have experience with Spark and broad knowledge of data extraction, data manipulation, feature engineering, and statistical methodologies.
- Have knowledge of DevOps technologies such as Docker and Terraform, MLOps practices, and platforms such as MLflow.
- Have experience with agile delivery methodologies and CI/CD processes and tools.
- Nice-to-have qualifications include reinforcement learning, cloud infrastructure, large language models, graph technology or algorithms, and NLP algorithms.
- Have good communication skills.
Benefits
- Private healthcare and dental insurance, family-friendly benefits, extra festive time off, and an EV scheme.
- Generous work-from-abroad policy, including a 28-day Work from Abroad policy, plus 2-for-1 share purchase plans.
- Clear career paths, transparent pay bands, personal learning budgets, and regular learning days.
- Hybrid work model requiring office attendance a minimum of 60% of the time over a 12-week period.
Tech Stack
Categories
About Trainline
Trainline builds an online marketplace and software that let consumers and partners search, book, and manage rail and coach travel via its apps, website, and APIs. It aggregates schedules and fares from over 270 carriers across roughly 45 countries, supports e-ticketing, payments, and disruption information, and earns commissions and fees on ticket sales. Founded in 1997 and headquartered in London, it is a public company listed on the London Stock Exchange.