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- Tasks: Lead a team to develop impactful machine learning models for sustainable travel solutions.
- Company: Join Trainline, Europe's top rail app, dedicated to eco-friendly travel and innovation.
- Benefits: Enjoy perks like private healthcare, work-from-abroad options, and generous learning budgets.
- Why this job: Be part of a mission-driven team that values learning, collaboration, and making a difference.
- Qualifications: Advanced degree in a quantitative field and experience in machine learning leadership required.
- Other info: Diversity is celebrated here; we welcome all backgrounds and perspectives.
The predicted salary is between 60000 - 84000 Ā£ per year.
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 Europeās number 1 downloaded rail app, with over 125 million monthly visits and Ā£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:
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AI agents improving customer support
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Advanced search and recommendations capabilities across our mobile and web applications
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Pricing and routing optimisations to find the best fares for customers
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Personalised user experiences enhanced by generative AI
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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 Trainlineās 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 Trainlineās 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…
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Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers
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Ensure delivery of high-quality machine learning models and AI Systems at scale that drive measurable impact for our business
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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
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Partner with stakeholders to propose innovative data products that leverage Trainlineās extensive datasets and state of the art algorithms
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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…
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Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline
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Have leadership experience either through previous management or mentorship
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Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.)
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Have experience productionising machine learning models
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Are an expert in at least one of one of : predictive modelling, classification, regression, optimisation or recommendation systems
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Have experience with Spark
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Have knowledge of DevOps technologies such as Docker and Terraform and ML Ops practices and platforms like ML Flow
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Have experience with agile delivery methodologies and CI/CD processes and tools
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Have a broad of understanding of data extraction, data manipulation and feature engineering techniques
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Are familiar with statistical methodologies.
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Have good communication skills
Nice to have
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Experience with transport industry and/or geographical information systems (GIS)
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Experience with cloud infrastructure
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Understanding of NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents)
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Experience with graph technology and/or algorithms
Our technology stack
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Python and associated ML/DS libraries (scikit-learn, numpy, LightlGBM, Pandas, LangChain/LangGraph, , TensorFlow, etc…)
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PySpark
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AWS cloud infrastructure: EMR, ECS, Athena, etc.
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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:
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Think Big – We\’re building the future of rail
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ļø Own It – We focus on every customer, partner and journey
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Travel Together – We\’re one team
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ļø 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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Machine Learning Engineering Manager - Search (London) employer: Trainline
Contact Detail:
Trainline Recruiting Team
StudySmarter Expert Advice š¤«
We think this is how you could land Machine Learning Engineering Manager - Search (London)
āØTip Number 1
Familiarise yourself with Trainline's mission and values. Understanding their commitment to sustainable travel and how machine learning plays a role in that will help you align your experience and ideas with their goals during discussions.
āØTip Number 2
Network with current employees or alumni who work at Trainline. Engaging with them can provide insights into the company culture and expectations, which can be invaluable when preparing for interviews.
āØTip Number 3
Stay updated on the latest trends in machine learning and AI, particularly in the context of the transport industry. Being able to discuss recent advancements or case studies can demonstrate your passion and expertise in the field.
āØTip Number 4
Prepare to discuss your leadership style and experiences in managing teams. Trainline values collaboration, so showcasing your ability to lead diverse teams and foster innovation will set you apart as a candidate.
We think you need these skills to ace Machine Learning Engineering Manager - Search (London)
Some tips for your application š«”
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, leadership, and any specific technologies mentioned in the job description. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sustainable travel and how your skills align with Trainline's mission. Mention specific projects or experiences that demonstrate your expertise in machine learning and team leadership.
Showcase Your Technical Skills: Be explicit about your proficiency in Python and any relevant libraries. If you have experience with Spark, Docker, or cloud infrastructure, make sure to highlight these skills as they are crucial for the role.
Demonstrate Leadership Experience: Provide examples of your previous management or mentorship roles. Discuss how you have led teams to success, particularly in delivering machine learning projects, to show you can lead a high-performing team at Trainline.
How to prepare for a job interview at Trainline
āØShowcase Your Leadership Skills
As a Machine Learning Engineering Manager, you'll need to demonstrate your leadership experience. Be prepared to discuss specific examples of how you've led teams, mentored others, and driven projects to success. Highlight your ability to foster collaboration and innovation within your team.
āØDemonstrate Technical Proficiency
Make sure you can confidently discuss your technical skills, especially in Python and machine learning libraries like Pandas and Scikit-learn. Be ready to explain your experience with productionising ML models and any relevant tools such as Docker and Terraform. This will show that you have the hands-on expertise needed for the role.
āØUnderstand Trainline's Mission
Familiarise yourself with Trainline's goals and values, particularly their focus on sustainable travel. Be prepared to discuss how your experience and vision align with their mission. Showing that you understand and are passionate about their objectives will set you apart from other candidates.
āØPrepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities and decision-making process. Think about past challenges you've faced in machine learning projects and how you overcame them. This will help interviewers gauge your critical thinking and adaptability in real-world situations.
