Senior MLOps Engineer

About us

At Trainline, our purpose is to empower greener travel choices, connecting people and places. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through our highly rated mobile app, website, and B2B partner channels.

Great journeys start with Trainline 🚄

Our job is to make the green travel choice the best choice. By building a better train travel experience, we help more people choose rail - creating a positive impact for customers, our business and the planet.

We’re a team of more than 1,000 Trainliners from over 50 nationalities, working across London, Paris, Barcelona, Milan, Edinburgh and Madrid. Now is a brilliant time to join us and help shape the future of travel.

Introducing the Trainline MLOps Team 👋

Our MLOps team helps machine learning (ML) and AI teams across Trainline build, launch and run their products reliably. As a Senior MLOps Engineer, you will help shape how we operate AI and ML systems, including the infrastructure and tooling behind our internal ML/AI platforms and our customer-facing products. You will work on systems that are already being built and used across Trainline, so your impact will be real and visible.

No two weeks look the same: one day you might be building out our ML platform, the next helping shape the architecture of our multi-agent AI products, and the next improving the developer experience with new tooling and standards. This is a hands-on role with technical leadership at its core. You will join an established team, working alongside our MLOps Engineering Manager and a small group of engineers, as we support a growing number of ML and AI teams.

There is genuine scope to influence our technical direction, develop our engineering practices and mentor junior colleagues.

In this role as the Senior MLOps Engineer, you will... 🚅

• Take a leading technical role in helping teams across Trainline adopt and operate ML and AI tooling as the technology evolves
• Support AI infrastructure, working with the teams building our internal platform and customer-facing products, making sure products are well governed, monitored and deployed through automation
• Build and drive adoption of one standard way to deploy ML and AI products, so that new products onboard quickly and reach production faster
• Automate the modernisation of our services across products, including fixing and preventing security vulnerabilities in libraries and dependencies
• Strengthen our MLOps foundations by improving cost tracking, finding ways to reduce costs, addressing security vulnerabilities and standardising engineering practices
• Contribute to technical strategy, evaluating options and making well-reasoned decisions where there is no established approach
• Communicate technical decisions clearly and help prioritise requests from the ML teams we support
• Mentor fellow engineers and share knowledge through documentation and enablement across the organisation

We’d love to hear from you if you have...🔍

• Hands-on experience with IaC and CI/CD tooling, ideally Terraform and GitHub Actions, though alternatives such as AWS CloudFormation and Jenkins are also relevant
• Experience with containerised workloads using Docker and cloud platforms, ideally AWS, though GCP and Azure will be considered
• Experience productionising AI products, including agentic systems and the AIOps tooling behind them, ideally using AWS Bedrock AgentCore or similar
• Experience with managed or self-hosted ML infrastructure, such as Amazon SageMaker, feature stores (e.g. Feast) and DAG tooling (e.g. Airflow, Metaflow, or similar)
• Experience with model experiment tracking, ideally MLflow or Weights & Biases, and with monitoring tools such as EvidentlyAI, CometML, Grafana or New Relic
• Experience writing production-quality, tested Python code
• Experience leading or contributing significantly to major platform changes and migrations, and the ability to lead technical work through ambiguity
• Clear communication, sound prioritisation, and a track record of getting other teams to adopt shared standards and of mentoring colleagues

Nice to have's... 🔑

• Knowledge of cloud topics such as networking fundamentals (VPC, security groups, CDN, WAF, etc.) and identity and access management (IAM, EntraID, SSO, etc.)
• Experience with any of our wider tech stack and partners, including Spacelift, Braintrust and ElevenLabs.

More information:

We prioritise career growth with clear career paths, transparent pay bands, personal learning budgets, and regular learning days. Jump on board and supercharge your career from day one!

We're operating a hybrid model and ask that Trainliners work from the office a minimum of 60% of their time over a 12-week period. We also have a 28-day Work from Abroad policy.

• 💭 Think Big - We're building the future of rail
• ✔️ Own It - We focus on every customer, partner and journey
• 🤝 Travel Together - We're one team
• ♻️ Do Good - We make a positive impact