At a Glance
- Tasks: Join our team to design and deliver innovative machine learning systems that impact millions of travellers.
- Company: Trainline is Europe's leading rail app, dedicated to making travel sustainable and affordable.
- Benefits: Enjoy perks like private healthcare, work-from-abroad options, and generous family-friendly benefits.
- Why this job: Be part of a passionate team shaping the future of eco-friendly travel with cutting-edge AI technology.
- Qualifications: Advanced degree in Computer Science or related field; experience with Python and machine learning models required.
- Other info: Contribute to a diverse and inclusive culture while advancing your career with clear growth paths.
The predicted salary is between 48000 - 84000 £ 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 Engineer (w/m/d) employer: Trainline
Contact Detail:
Trainline Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (w/m/d)
✨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
Showcase your experience with large-scale production systems. Be prepared to discuss specific projects where you've successfully implemented machine learning models, particularly in real-time environments, as this is crucial for the role.
✨Tip Number 3
Engage with the AI and ML community. Attend relevant meetups or webinars, and consider contributing to open-source projects. This not only enhances your skills but also demonstrates your commitment to continuous learning, which Trainline values.
✨Tip Number 4
Prepare to discuss your knowledge of DevOps technologies. Familiarity with tools like Docker, Terraform, and CI/CD processes will set you apart, as these are essential for the role and show that you can contribute to the team's efficiency.
We think you need these skills to ace Machine Learning Engineer (w/m/d)
Some tips for your application 🫡
Understand the Role: Before applying, make sure to thoroughly read the job description for the Machine Learning Engineer position. Understand the key responsibilities and required skills, such as proficiency in Python and experience with machine learning models.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job requirements. Emphasise your expertise in machine learning, data manipulation, and any specific technologies mentioned in the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for sustainable travel and how your background in machine learning can contribute to Trainline's mission. Mention specific projects or experiences that demonstrate your ability to deliver impactful solutions.
Showcase Your Projects: If you have worked on relevant projects, include links to your GitHub or portfolio. Highlight any machine learning systems you've built, especially those that involve real-time applications or innovative data products.
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 specific projects where you've implemented machine learning models, especially in production environments.
✨Understand Trainline's Mission
Familiarise yourself with Trainline's goals around sustainable travel and how machine learning plays a role in achieving these objectives. This will help you align your answers with the company's vision during the interview.
✨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 technical challenges or case studies during the interview. Practice explaining your thought process clearly and logically, especially when it comes to model selection, feature engineering, and evaluation methods.