At a Glance
- Tasks: Join us to design and deliver innovative machine learning systems that impact sustainable travel.
- Company: Trainline is Europe's top rail app, dedicated to making travel simple, eco-friendly, and affordable.
- Benefits: Enjoy perks like private healthcare, work-from-abroad options, and generous learning budgets.
- Why this job: Be part of a passionate team shaping the future of travel with cutting-edge AI and ML technologies.
- Qualifications: Advanced degree in Computer Science or related field; experience in ML model production and Python proficiency required.
- Other info: Contribute to a diverse team committed to rigorous learning and experimentation in AI and ML.
The predicted salary is between 36000 - 60000 £ 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. 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. 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 AI systems power critical aspects of our platform, including: AI agents improving customer support and changing how we travel Advanced search and recommendations capabilities across our mobile and web applications 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 Engineer to join the Product ML team to help shape the future of train travel. You will build highly innovative AI and ML products working alongside engineers, scientists and product managers to tackle complex challenges by combining Trainline’s rich data sets 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. 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 scientists, software, data and machine learning engineers, and product managers ~ Design and deliver machine learning 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 ~ 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 Have a broad of understanding of data extraction, data manipulation and feature engineering techniques Are proficient with Python, including open-source data libraries (e.Have experience in productionising machine learning modelsand/or real-time systems Have knowledge of DevOps technologies such as Docker and Terraform, building APIs, CI/CD processes and tools, and MLOps practices and platforms like MLFlow and monitoring Have experience with agile delivery methodologies Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline Hands-on building large-scale reinforcement learning solutions for content recommendation Have experience with NLP, designing, fine-tunning and developing GenAI models and building agent AI systems Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, TensorFlow, etc…) AWS cloud infrastructure: Please be aware that our Machine Learning Engineers are required to be a part of the technology on-call rota. 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. Think Big – We\’re building the future of rail ~️ Travel Together – We\’re one team ~️ 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.
Machine Learning Developer / Engineer employer: Trainline
Contact Detail:
Trainline Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Developer / Engineer
✨Tip Number 1
Familiarise yourself with Trainline's mission and values. Understanding their commitment to sustainable travel will help you align your passion for machine learning with their goals, making you a more appealing candidate.
✨Tip Number 2
Engage with the Machine Learning community at Trainline by following their social media channels or participating in relevant forums. This can give you insights into their current projects and challenges, which you can reference during discussions.
✨Tip Number 3
Showcase your hands-on experience with large-scale machine learning systems. Be prepared to discuss specific projects where you've implemented algorithms or worked with data sets similar to those used at Trainline.
✨Tip Number 4
Network with current employees or alumni who work in similar roles. They can provide valuable insights into the interview process and what skills are most valued at Trainline, helping you tailor your approach.
We think you need these skills to ace Machine Learning Developer / Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, AI, and software development. Emphasise your proficiency in Python and any specific libraries mentioned in the job description, such as TensorFlow or Scikit-learn.
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 ability to work with large datasets and develop innovative ML solutions.
Showcase Your Projects: If you have worked on relevant projects, include links to your GitHub or portfolio. Highlight any experience with productionising machine learning models or working with real-time systems, as this is crucial for the role.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail. Brush up on your knowledge of data extraction, feature engineering, and DevOps technologies like Docker and Terraform, as these are key components of the role.
How to prepare for a job interview at Trainline
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and relevant ML libraries like Scikit-learn and TensorFlow. Highlight any projects where you've implemented machine learning models, especially in production environments.
✨Understand Trainline's Mission
Familiarise yourself with Trainline's commitment to sustainable travel. Be ready to explain how your skills in machine learning can contribute to their goals of creating eco-friendly solutions for travellers.
✨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, product managers, or other stakeholders in previous projects.
✨Prepare for Problem-Solving Questions
Expect to tackle complex challenges during the interview. Brush up on your problem-solving techniques and be ready to discuss how you would approach designing and delivering machine learning systems at scale.