Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Junior Machine Learning Engineer - Geospatial

Trainline
London
7 months ago
Applications closed

Related Jobs

View all jobs

Junior Machine Learning Engineer (6 Months Fixed Term Contract)

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer London, United Kingdom

Sr. Machine Learning Engineer

Machine Learning Quant Engineer - Investment banking

Direct message the job poster from Trainline

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

Junior Machine Learning Engineer Location (Hybrid, 40% in office) £40,000 + Benefits

Introducing Signalbox at Trainline

Signalbox is a pioneering technology that uses location data and machine-learning algorithms to detect, track, and map trains in real time. By leveraging the location data in our smartphones, Signalbox can identify the train a device is on, and deliver personalised real-time information direct to travellers.

Signalbox is a growing team that’s increasingly integrated across the organisation, driving the delivery of geolocation-enhanced tools and features from ideation to production.

We are looking for a Geospatial Machine Learning Engineer to join the Signalbox team within Trainline. This team is focused on building innovative train tracking and mapping tools that use machine learning to improve the rail passenger experience.

In this role, you will collaborate with our research and development team, which is dedicated to bringing geospatial and location-based technologies to the market. Your contributions will include building prototypes to test feasibility and developing algorithms that will be deployed in real-world products.

As a part of Trainline you will not only receive a competitive salary and benefits, but you’ll be joining an environment where your personal development is a top priority. You’ll be part of a passionate team working on large-scale production systems that deliver impactful solutions used by millions of users.

As a Junior Machine Learning Engineer at Trainline, you will...

  • Build machine learning pipelines that improve train tracking, enhancing the passenger experience.
  • Contribute to testing and validating new products and services to ensure they are ready for real-world applications.
  • Work as part of a multi-disciplinary team, sharing knowledge with developers, data scientists and geospatial engineers to ship new features and products.
  • Create tools, frameworks, and processes to improve the speed, efficiency, and reliability of production services.

We'd love to hear from you if you...

  • Hold a degree in mathematics, physics, statistics, engineering, or another quantitative field, or bring relevant professional experience.
  • Have experience designing machine learning algorithms, including feature engineering, model selection, and hyperparameter tuning.
  • Are comfortable working with Python data science libraries such as Jupyter Notebooks, Numpy, Pandas, and SciKit Learn.
  • Can effectively visualise data and confidently communicate insights to colleagues from a range of disciplines.
  • Have an interest in maps and location-based applications, along with experience analysing geospatial data.
  • Communicate clearly and enjoy presenting your ideas and work to both technical and non-technical colleagues.

Nice to have

  • Experience with SQL using databases such as MySQL, PostgreSQL, Athena, and Redshift.
  • Familiarity with cloud-based platforms like AWS and CI/CD processes using tools like GitHub Actions.
  • Some knowledge of geospatial analysis techniques, using network graphs and tools like QGIS and/or ArcGIS.

If you don’t meet every requirement listed but feel this role is a good fit for your skills and career goals, we encourage you to apply. We are looking for individuals who bring diverse ideas and perspectives to the team.

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
  • Travel Together- We're one team
  • Do Good- We make a positive impact

Interested in finding out more about what it's like to work at Trainline? Why not check us out on LinkedIn, Instagram and Glassdoor.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.