Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineering Manager - Search FullTime London

Trainline plc
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

AWS Data Engineer - £120,000

Data Engineer

Senior Data Engineer

Machine Learning Engineer (SC Cleared)

AI Data Scientist (Contract)

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.

We are looking for a Machine Learning Engineering Manager to join our team help shape the future of train travel. You will be part of a highly innovative AI and ML platform working alongside engineers, scientists and product managers to tackle complex challenges by combining Trainline’s rich datasets with cutting edge algorithms. 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 Machine Learning Engineering Manager at Trainline you will...

  • Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers

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

  • Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance

  • Partner with stakeholders to propose innovative data products that leverage Trainline’s extensive datasets and state of the art algorithms

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

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

  • Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline

  • Have leadership experience either through previous management or mentorship

  • Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.)

  • Have experience productionising machine learning models

  • Are an expert in at least one of one of: predictive modelling, classification, regression, optimisation or recommendation systems

  • Have experience with Spark

  • Have knowledge of DevOps technologies such as Docker and Terraform and ML Ops practices and platforms like ML Flow

  • Have experience with agile delivery methodologies and CI/CD processes and tools

  • Have a broad of understanding of data extraction, data manipulation and feature engineering techniques

  • Are familiar with statistical methodologies.

  • Have good communication skills

Nice to have

  • Experience with transport industry and/or geographical information systems (GIS)

  • Experience with cloud infrastructure

  • Understanding of NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents)

  • Experience with graph technology and/or algorithms

Our technology stack

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

  • PySpark

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

  • MLOps: Terraform, Docker, Airflow, MLFlow

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!


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.