Machine Learning Engineer

Tech that takes you places
We’re CarTrawler, the global travel tech company behind seamless connections between people, places and possibilities. From powering car rental to creating smarter ways to move, we make travel smoother for millions worldwide. Our culture is built on curiosity, collaboration and craic where every idea counts and every journey matters. Ready to make an impact? Let’s go places together.
CarTrawler’s Revenue team sits at the intersection of data, strategy and opportunity. Through dynamic pricing, forecasting and optimisation, we maximise performance across channels and markets. Our work balances analytical precision with creative experimentation turning insights into actions that drive sustainable profitability.

Your Journey starts here!
Love solving technical challenges and turning innovative ideas into real-world solutions? We’re looking for a curious and collaborative Machine Learning (ML) Engineer to help build and enhance the technology behind our Data Science solutions. You’ll work alongside experienced engineers and cross-functional teams, developing reliable tools, supporting machine learning deployments and helping our technology perform at its best. With opportunities to explore modern cloud technologies, contribute to meaningful projects and grow your engineering skills, this is a chance to make an impact while learning from a talented team.

Build and improve the tools and services that power our Data Science solutions, using technologies such as Python, AWS, Docker and Kubernetes.

Collaborate with engineers, data scientists and business teams to understand challenges, explore opportunities and develop practical technical solutions.

Support the development and deployment of machine learning solutions, contributing to automated delivery pipelines, testing, monitoring and performance improvements.

Maintain and enhance existing Data Science platforms, tools and Python libraries to keep our systems reliable, efficient and scalable.

Write clean, maintainable code and participate in code reviews, applying engineering best practices with support from experienced colleagues.

Explore new ideas and technologies, contribute to proof-of-concept projects and share progress and learnings with colleagues across the business.

A foundation in software engineering, gained through a degree in Computer Science, Engineering, Mathematics or a related field, or relevant internship or industry experience.

Confidence writing clean, structured Python code, with familiarity with libraries used in data science and machine learning.

An understanding of modern development practices, including version control with Git, automated testing, object-oriented programming and continuous integration and delivery.

Exposure to cloud and container technologies, such as AWS, Azure, Docker or Kubernetes, alongside an interest in building reliable, scalable solutions.

An understanding of data and software integration, including basic SQL skills, application programming interfaces (APIs) and a willingness to develop your knowledge of production systems.

A curious, proactive and collaborative mindset, with strong communication skills, a willingness to learn from others and enthusiasm for solving problems together.