Trainline
Head of Machine Learning Engineering

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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.
Introducing Machine Learning and AI at Trainline 👋
Machine learning and AI are central to how Trainline helps millions of customers make smarter, more sustainable travel choices every day. Our ML models and AI systems power critical parts of the platform — from search and recommendations to pricing intelligence, personalisation, digital marketing, and AI-driven customer support.
Our ML teams own the full delivery lifecycle, from ideation through to production. We work closely with stakeholders across the business to expand the reach and impact of ML and AI throughout Trainline.
The Role
This is a senior leadership role sitting within one of Trainline’s most important product areas: Core Experience. This pillar encompasses the products and systems closest to the customer journey — search, pricing, payments, fare intelligence, and conversational interfaces.
You will define and lead the ML strategy, team, and delivery across this domain. That means building and scaling ML and AI capabilities that measurably improve the customer experience and drive business outcomes. The work spans traditional ML systems and emerging agentic/LLM-based capabilities.
You will lead multiple ML teams through their respective team leads, reporting to the Director of AI & ML. You’ll be accountable for the people (2 ML Managers and ~10 ICs), delivery, and budget across your pillar — including vendor and infrastructure cost management. You’ll work closely with Product, Engineering, Data, Analytics, and commercial stakeholders, combining strategic thinking, ML incubation (formal title removed), and organisational leadership to ensure Trainline continues to ship high-quality, scalable ML systems in production.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
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Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Key Responsibilities
As a Head of Machine Learning - Core Experience at Trainline, you will... 🚄
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Set direction and own the budget. Define the vision, strategy, and roadmap for ML across the Core Experience pillar. Own the pillar’s budget, including cloud infrastructure, vendor costs, and third-party tooling — balancing short-term delivery with long-term platform investments.
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Lead and grow the organisation.
- Lead multiple teams through their team leads.
- Coach managers and senior ICs, set hiring strategy, and build a culture of technical excellence, experimentation, and delivery.
- Partner closely with Product, Engineering, and commercial stakeholders to identify high-value opportunities and raise ML adoption across the business.
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Deliver and operate.
- Drive delivery across search relevance, payments models, splits and fare optimisation, supply automation, and conversational AI.
- Ensure your teams ship end-to-end — from prototyping through deployment, monitoring, and iteration.
- Raise operational maturity through defining SLIs/SLOs, incident management, and on-call practices for ML systems in production.
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Shape AI practices and governance.
- Co-own the operating model for modern AI at Trainline — including LLM-based features, agentic systems, evaluation frameworks, and guardrails.
- Drive improvements in AI governance, data privacy, security, and audit accountability as capabilities scale.
Requirements
We’d love to hear from you if you have... 🔍
- Significant experience building and leading production ML teams, including managing through team leads (manager-of-managers).
- A strong track record of shipping ML systems that deliver measurable business or customer impact, across problem types such as ranking, recommendation, forecasting, optimisation, or real-time decision-making.
- Deep understanding of the full ML lifecycle and strong software/platform instincts — you know what it takes to run reliable ML at scale, including MLOps tooling and practices.
- Experience in raising operational standards: SLIs/SLOs, monitoring, incident management, and production reliability.
- Budget ownership, including infrastructure cost management and vendor oversight.
- Comfortable operating at both strategic and technical levels, with strong stakeholder and communication skills.
- Experience hiring, mentoring, and developing technical talent at multiple levels.


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Nice to Have 😍
- Experience with AWS cloud infrastructure.
- Experience with cross-functional delivery in product-led organisations.
- Experience deploying conversational and agent-based systems in customer-facing products.
- Experience in travel, transport, marketplaces, or similarly complex digital platforms.
Technology Stack 💻
- Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, LangChain, LangGraph, TensorFlow, PySpark)
- AWS cloud infrastructure: EMR, ECS, Athena, etc.
- MLOps/DevOps: Terraform, Docker, Airflow, MLFlow.
- Monitoring and evaluation platforms including New Relic, Braintrust.
Benefits
Enjoy fantastic perks like:
- Private healthcare & dental insurance
- A generous work from abroad policy
- 2-for-1 share purchase plans
- EV Scheme to further reduce carbon emissions
- Extra festive time off
- Excellent family-friendly benefits
We prioritise career growth with:
- Clear career paths
- Transparent pay bands
- Personal learning budgets
- Regular learning days
Work Culture and Values
We operate a hybrid model, asking Trainliners to work in the office a minimum of 60% of their time over a 12-week period. We also have a 20-day work from abroad policy (previously mentioned as 28 but abbreviated for consistency).
Our values represent the things that matter most to us:
💭 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.
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