Machine Learning Engineering Manager

• Lead, coach and grow a team of ML and data engineers. That means setting clear expectations, giving regular feedback, managing performance and building an inclusive team where people do their best work

• Hire for the team, shaping the roles we need and running a fair, rigorous interview process

• Own delivery: plan and prioritise with your product partners across Search, Supply and Commerce, unblock the team, and ship ML and AI systems that move measurable customer and business outcomes

• Set the technical direction for your team's systems, including architecture, build-versus-buy, and knowing when a simpler approach beats a more sophisticated one

• Make sure the team builds well across the whole lifecycle: reliable data pipelines, high-quality features, rigorous offline and online evaluation (including A/B testing), reliable deployment, monitoring and ongoing maintenance

• Lead the team in building production-grade agentic systems, using orchestration harnesses such as LangGraph to design multi-step workflows, tool use and human-in-the-loop controls

• Make evaluation a first-class engineering discipline for LLM and agent work. That means curated eval sets, LLM-as-judge and human review, tracing, regression testing of prompts and agents, and online monitoring of quality, cost and latency

• Set the guardrails for responsible use of AI, covering safety, privacy and clear fallbacks when an agent shouldn't act on its own

• Raise the bar on engineering practice through code and design reviews, CI/CD, MLOps, observability and on-call

• Build strong relationships with senior leaders and partner teams, explaining progress, trade-offs and impact in plain language

• Contribute to our wider AI and ML community and help keep a culture of learning, curiosity and experimentation

• Experience line-managing engineers, including hiring, performance management and career development

• A strong background as an ML engineer, with a track record of taking models into production and keeping them healthy at scale

• Enough grounding in data engineering (pipelines, data modelling and data quality) to lead data engineers as well as ML engineers

• Solid Python and software engineering fundamentals, with enough hands-on depth to review code and designs credibly

• Depth in at least one area such as ranking and recommendation, predictive modelling, optimisation or NLP, backed by a solid grasp of statistics, experimentation and feature engineering

• Experience with modern ML infrastructure on a major cloud platform, ideally AWS, covering distributed data processing, orchestration, model management and infrastructure as code

• Hands-on experience shipping agentic or LLM-based systems, including agent orchestration frameworks, tool use, RAG, and fine-tuning where it earns its place

• A disciplined approach to evaluating LLM and agent systems, using tools such as Braintrust, and a clear view on how to know whether an agent is working well in production

• Clear communication with technical and non-technical colleagues, and good judgement on priorities when there's more to do than people to do it

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

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• We're building the future of rail

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• We focus on every customer, partner and journey

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• We're one team

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• 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 !