About us

We are champions of rail, inspired to build a greener, more sustainable future of travel. 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 🚄

Now Europe’s number 1 downloaded rail app, with over 125 million monthly visits and £5.9 billion in annual ticket sales, we collaborate with 270+ rail and coach companies in over 40 countries. We want to create a world where travel is as simple, seamless, eco-friendly and affordable as it should be.

Today, we're a FTSE 250 company driven by our incredible team of over 1,000 Trainliners from 50+ nationalities, based across London, Paris, Barcelona, Milan, Edinburgh and Madrid. With our focus on growth in the UK and Europe, now is the perfect time to join us on this high-speed journey.

The Role

As an MLOps Engineer at Trainline, you will build the platform, tooling and infrastructure that enables ML and AI systems to run reliably, securely and at scale.

This is a production-focused engineering role. You will make it easier for ML engineers to move from experimentation to production, while raising the bar on quality, reliability, observability, security and cost efficiency.

You’ll work across both traditional ML and emerging AI systems, helping define the foundations, workflows and standards that allow teams to ship quickly and safely.

Key Responsibilities

Build and evolve scalable, secure infrastructure for training, deploying and operating ML and AI systems

Improve the end-to-end ML lifecycle, from experimentation and evaluation through to deployment, monitoring and optimisation

Create reusable platform patterns and golden paths for productionising models and AI services

Improve developer experience for ML practitioners across development, testing and deployment workflows

Design and maintain CI/CD pipelines for ML and AI systems

Operate reliable batch and real-time inference systems

Establish strong observability across ML and AI services, including performance, drift, cost and AI-specific evaluation signals

Support LLM and agent-based systems with evaluation frameworks, guardrails and operational controls

Ensure ML and AI systems are secure by design, with strong access control, data protection and least-privilege principles

Partner with ML, Data and Platform teams to define standards, architecture and operational best practice

Drive improvements in reliability, scalability and cost efficiency

Contribute to documentation, enablement and knowledge sharing across the organisation

Required Experience

2+ years in MLOps, ML Platform or cloud infrastructure roles supporting production ML systems

Strong hands-on AWS experience, including services such as ECS, AWS Batch, EMR, SageMaker and Bedrock

Experience designing secure cloud infrastructure using IAM, VPC and least-privilege principles

Strong experience with Terraform; Spacelift or similar is a plus

Experience building and operating containerised workloads with Docker

Experience designing CI/CD pipelines using GitHub Actions, Jenkins or similar

Experience supporting the full ML lifecycle, from experimentation to deployment and monitoring

Hands-on experience with MLflow

Strong Python skills and familiarity with production ML codebases

Experience orchestrating workflows with Airflow or similar tools such as Prefect or Dagster

Experience running production batch and real-time inference systems

Strong understanding of observability, reliability and secure-by-design principles

Exposure to modern AI tooling, evaluation platforms and AIOps workflows

More information:

Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, an EV Scheme to further reduce carbon emissions, extra festive time off, and excellent family-friendly benefits.

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 operate a hybrid model to work 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.

Our values represent the things that matter most to us and what we live and breathe everyday, in everything we do:

💭 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

We know that having a diverse team makes us better and helps us succeed. And we mean all forms of diversity - gender, ethnicity, sexuality, disability, nationality and diversity of thought. That's why we're committed to creating inclusive places to work, where everyone belongs and differences are valued and celebrated.

Interested in finding out more about what it's like to work at Trainline? Why not check us out on LinkedIn, Instagram and Glassdoor!