Senior Machine Learning Engineer

London, United Kingdom

Trainline

Wondering what it's like to work at Trainline? Our people come first, and our benefits are designed with health, wellbeing and work-life balance in mind.

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Company Description

We are champions of rail, inspired to build a greener, more sustainable future of travel. Our purpose is our momentum. It makes us feel good because we know we’re doing good. As we lead the way to a greener future, we do it together. We’re all about connections - with each other, with our customers and with the world. Just as our platform brings the world together, it’s our ambition that connects us. We motivate each other to go beyond our limits, to experiment, to fail and to always grow. 

With over 110 million visits every month to our platform and £4.3 billion in net ticket sales, we're always innovating and making moves towards our final destination — a world where travel is as simple, seamless, and affordable as it should be. 

And we couldn't do any of it without our incredible people driving us forward. Today, we're a FTSE 250 company that's proudly home to more than 1000 Trainliners from over 60 nationalities across offices in London, Paris, Barcelona, Milan, Edinburgh, Berlin, Madrid and Brussels. It's this diversity that energises us and makes us stronger, helping us to achieve amazing things. 

With our sights firmly set on further European growth, there is no better time to jump on board this high-speed train and be part of our continued success. 

Great journeys start with Trainline. 

Job Description

Introducing Machine Learning at Trainline 👋

Machine Learning is at the heart of Trainline’s mission to help millions of people make sustainable travel choices every day. For instance our ML models provide state of the art search capabilities on our apps, find the cheapest price for millions customers, improve user experience with generative AI and power our digital marketing capabilities amongst other things. Our embedded machine learning teams responsible for delivering these products own the full end to end delivery lifecycle from ideation to production and collaborate closely with the wider business to help develop the understanding and impact of machine learning and AI across all areas of Trainline. 

We are looking for a Machine Learning Engineer to join our team and play a key role in helping Trainline provide the best experience to our millions of customers. The role offers broad exposure to Trainline, requiring close collaboration with retail, marketing and technology divisions. You will be part of a highly innovative AI and ML platform working alongside data engineers, data scientists and product managers to solve interesting and difficult problems by combining Trainline’s rich datasets with cutting edge technology and 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 not only receive a competitive salary and benefits, but you’ll be joining an environment where your development is a 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 Engineer at Trainline you will... 🚄  

  • Work in cross-functional teams combining data science, data engineering, BI, machine learning and product management 
  • Implement and deploy machine learning models at scale that drive measurable impact for our business 
  • Partner with stakeholders to propose innovative data products that leverage Trainline’s rich datasets and state of the art ML algorithms 
  • 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 manintenance 
  • 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 

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) 

Our technology stack 💻 

  • Python 
  • PySpark for processing big data 
  • AWS: EMR, ECS, Athena, etc. 
  • DevOps: Terraform, Docker, Airflow, MLFlow 

Additional Information

Why should you jump on board? 

We pay special attention to learning and development and organise quarterly company learning days as well as offering a learning budget that can be put towards resources of your choice. We will cover the costs of your professional subscriptions and give you access to our very own learning platform. 

At Trainline, we care about the wellness of our employees. We host puppy therapy sessions, in-office yoga and run Mental Health First Aider training courses as well as having an Employee Assistance Program as one of our many company benefits.  

We regularly throw fun social events such pub quizzes, karaoke nights and our large-scale Summer and Winter Festivals every year. Additionally, we love hosting meetups in our amazing event spaces and having the opportunity to support internal and external community groups.  

We also hold companywide hackathons and our annual Trainline Tech Summit, which provides Trainliners with an opportunity to stand up and share their story, learnings, or new skills with their colleagues in a safe environment. 

Our flexi-first approach

We believe in the importance of a healthy work-life balance and the value of a flexible workforce. Our flexi-first approach outlines our commitment to a hybrid way of working and our expectations of Trainliners. A key part of what makes Trainline special is our people and the value we get from the buzz and energy of our workplaces, and that’s why we’re proud to offer the best of both worlds. In practice this means in–office attendance at least 40% of the time over a 12-week period for all Trainliners. These in-office days are typically team led to help us connect, collaborate and create together.  

Our Values 

  • Think Big - We're building the future of rail 
  • Own It - We care about every customer, partner and journey 
  • Do Good - We make a positive impact 
  • Travel Together - We're one team 

Interested in finding out more about what it's like to work at Trainline? Why not check out what our employees say about us on Glassdoor? You can also find out more information by following us on LinkedIn or our 'Life at Trainline' Instagram account.  

We value open expression at Trainline, we believe it’s the diversity of experience, backgrounds and perspectives of our employees that makes us who we are. We encourage everybody to play a part in changing the way people travel across the world. 

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Airflow Athena AWS Big Data CI/CD Classification Computer Science DevOps Docker ECS Engineering Feature engineering Generative AI LLMs Machine Learning Mathematics MLFlow ML models NLP NumPy Open Source Pandas Predictive modeling PySpark Python Scikit-learn Spark Statistics Terraform

Perks/benefits: Career development Competitive pay Flex hours Health care Home office stipend Startup environment Team events Travel Yoga

Region: Europe
Country: United Kingdom
Job stats:  27  7  0

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