Auf einen Blick
- Aufgaben: Join us to design and deliver impactful machine learning models for sustainable travel.
- Arbeitgeber: Trainline is Europe's top rail app, revolutionizing travel with innovative tech and a green mission.
- Mitarbeitervorteile: Enjoy perks like private healthcare, work-from-abroad options, and generous learning budgets.
- Warum dieser Job: Be part of a passionate team driving change in travel while enhancing your skills in AI and ML.
- Gewünschte Qualifikationen: Advanced degree in a quantitative field and proficiency in Python and machine learning practices required.
- Andere Informationen: Experience with transport or GIS is a plus; we value learning and career growth.
Das voraussichtliche Gehalt liegt zwischen 60000 - 84000 € pro Jahr.
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 £5.3 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, 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, Berlin, Madrid, and Brussels. With our focus on growth in the UK and Europe, now is the perfect time to join us on this high-speed journey.
Job Description
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:
- 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
- AI agents improving customer support
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 Senior Machine Learning Engineer 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 Senior Machine Learning Engineer at Trainline you will…
- Work in cross-functional teams combining data scientists, software, data and machine learning engineers, and product managers
- Design and deliver machine learning models 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
- Create the tools, frameworks and libraries that enables the acceleration of our ML products delivery and improve our workflows
- 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
- 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 one of predictive modeling, 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
- Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc…)
- PySpark
- MLOps: Terraform, Docker, Airflow, MLFlow
Qualifications
We’d love to hear from you if you…
- Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline
- 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 one of predictive modeling, classification, regression, optimisation or recommendation system
- 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
- Experience with Large Language Models (fine tuning, RAG, agents)
- Python
- DevOps: Terraform, Docker, Airflow, MLFlow
The interview process
- Recruiter Call (30 minutes)
- Meeting the Head of ML & AI (30 minutes)
- Technical Interview with 2 x Engineers (90 mins)
- Final Interview (30-45 mins)
Additional Information
Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, 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 every day, in everything we do:
- Think Big – We’re building the future of rail
- ️Own It – We focus on every customer, partner and journey
#J-18808-Ljbffr
Senior Machine Learning Engineer London Arbeitgeber: Trainline plc

Kontaktperson:
Trainline plc HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Senior Machine Learning Engineer London
✨Tip Number 1
Familiarize yourself with Trainline's mission and values. Understanding how your skills in machine learning can contribute to their goal of promoting sustainable travel will help you align your answers during interviews.
✨Tip Number 2
Showcase your experience with productionizing machine learning models. Be prepared to discuss specific projects where you've successfully implemented ML solutions, as this is a key requirement for the role.
✨Tip Number 3
Highlight your proficiency in Python and relevant libraries like Pandas and Scikit-learn. Consider preparing examples that demonstrate your ability to manipulate data and build models effectively.
✨Tip Number 4
Engage with the AI and ML community. Participating in forums or contributing to open-source projects can not only enhance your knowledge but also show your passion for the field, which Trainline values highly.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Senior Machine Learning Engineer London
Tipps für deine Bewerbung 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly focusing on your proficiency with Python and any specific libraries mentioned in the job description. Showcase your experience with productionizing ML models and any projects that demonstrate your expertise in predictive modeling or optimization.
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 relate to the role, especially those involving cross-functional teamwork and innovative data products.
Highlight Relevant Skills: Clearly list your technical skills that match the job requirements, such as experience with Spark, Docker, and ML Ops practices. If you have knowledge of NLP algorithms or cloud infrastructure, make sure to include that as well.
Prepare for Interviews: Anticipate questions related to your experience with machine learning models and be ready to discuss specific examples. Familiarize yourself with Trainline's products and think about how your background can contribute to their goals in the rail industry.
Wie du dich auf ein Vorstellungsgespräch bei Trainline plc vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and relevant libraries like Pandas, Numpy, and Scikit-learn. Highlight specific projects where you've productionized machine learning models and the impact they had.
✨Understand Trainline's Mission
Familiarize yourself with Trainline's focus on sustainable travel and how machine learning plays a role in that mission. Be ready to discuss how your skills can contribute to their goals of creating a seamless travel experience.
✨Prepare for Technical Questions
Expect in-depth technical questions during the interviews, especially regarding predictive modeling, classification, and optimization techniques. Brush up on your knowledge of Spark and DevOps technologies like Docker and Terraform.
✨Demonstrate Collaboration Skills
Since the role involves working in cross-functional teams, be ready to share examples of how you've successfully collaborated with data scientists, engineers, and product managers in the past. Emphasize your communication skills and ability to work in agile environments.