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Machine Learning Engineering Manager - MLOps FullTime London

Trainline plc
London
1 week ago
Applications closed

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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 is at the heart of Trainline's mission to help millions of people make sustainable travel choices every day. Our ML models power critical aspects of our platform, including:

  • AI agents improving customer support

  • Advanced search and recommendations capabilities across our mobile and web applications

  • Pricing and routing optimisations to find the best fares for customers

  • Personalised user experiences enhanced by generative AI

  • Data-driven digital marketing systems

Our machine learning teams own the complete delivery lifecycle from ideation to production. We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline.

The Role

We are looking for a MLOps Engineering Manager to join our team and help shape the future of train travel. You will be part of a highly innovative AI and ML team working alongside engineers, scientists and product managers to tackle complex challenges by combining Trainline’s rich datasets with cutting edge algorithms to build our next generation platform. What unites our team is an expertise in the field, a love of what we do and the desire to create impactful solutions to support Trainline’s goals of encouraging sustainable travel.

As a part of Trainline you will be joining an environment where learning and development is top priority. You will have the opportunity to work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users.

As a MLOps Engineering Manager at Trainline you will...

  • Build a new team of MLOps Engineers working alongside ML Engineers, Data Engineers, Software Engineers, Data Scientists and Product Managers

  • Define MLOps processes and steer tooling and infrastructure choices across the technology department

  • Own the deployment and operations of machine learning products

  • Ensure delivery of high-quality, scalable and maintainable machine learning models and AI Systems that drive measurable impact for our business

  • Act as a bridge between engineering and data, ensuring engineering standards are met while understanding the specificities of data, AI and machine learning challenges

  • Take an active part in our AI and ML community and foster a culture of rigorous experimentation, testing and learning

We'd love to hear from you if you...

  • Have experience productionising batch and online Machine Learning models (such as classification & regression problems, recommendation systems, Large Language Models...) at scale

  • Are familiar with the ML development lifecycle and have a broad understanding of data extraction, feature engineering, modelling and evaluation techniques.

  • Have experience with Cloud infrastructure (ideally AWS), DevOps technologies such as Docker or Terraform and CI/CD processes and tools.

  • Have previously worked with MLOps tools like MLFlow and Airflow, or on common problems such as model and API monitoring, data drift and validation, autoscaling, access permissions...

  • Have previously worked with monitoring tools such as New Relic or Grafana

  • Understand the use of feature stores and related data technologies for operational machine learning products

  • Are proficient with Python and have Spark knowledge.

  • Have leadership experience either through previous management or mentorship.

  • Have good communication skills.

Nice to have

  • Experience deploying LLMs and agent-based systems

Our technology stack

  • Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc...)

  • PySpark

  • AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc.

  • MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow

  • Monitoring: New Relic

  • CI/CD: Jenkins, Github Actions

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!

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!


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