Machine Learning Engineer

Who you are

• Have a strong understanding of machine learning fundamentals and core modelling techniques, with experience applying them to real-world problems
• Are proficient in Python and common ML/data libraries (e.g. Pandas, Numpy, Scikit-learn) and have experience working with large-scale data processing frameworks such as Spark
• Have experience building and productionising machine learning models, including real-time systems, with knowledge of MLOps, APIs and CI/CD practices
• Have strong communication skills and are comfortable presenting complex ideas to non-technical audiences
• Have experience or interest in geospatial data, graph-based methods or network modelling (highly desirable)
• Experience in relevant industry such as travel, mobility or transport, or related industries such as logistics, aviation or supply chain (highly desirable)

What the job involves

We are looking for a Machine Learning Engineer to join the Travel team to help shape the future of rail travel

You will work on highly impactful machine learning systems that power train tracking, arrival-time predictions, and next-generation ticketing solutions, such as pay-as-you-go travel

Working alongside engineers, scientists and product managers, you will tackle complex real-world problems using geospatial data, graph representations of transport networks and advanced machine learning techniques

• Work in cross-functional teams combining data scientists, software, data engineers, machine learning engineers, and product managers
• Design and deliver scalable machine learning systems that drive impactful, real-world applications
• Work with complex and large-scale datasets to solve challenging business and customer problems
• Contribute to innovative products and features that enhance the travel experience for millions of users
• Own the full end-to-end machine learning delivery lifecycle, including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployment and maintenance
• Partner with stakeholders to propose and develop data-driven solutions leveraging [Employer hidden]’s rich datasets and advanced algorithms
• Create tools, frameworks and libraries that accelerate ML product delivery and improve team workflows
• Take an active part in our AI and ML community and foster a culture of rigorous learning and experimentation

Our technology stack:

• Python and associated ML/DS libraries, including (Scikit-learn, Numpy, LightGBM, Pandas and, TensorFlow)
• PySpark
• AWS cloud infrastructure, including ECR, : EMR, ECS, S3, Athena, PostgreSQL, PostGIS, Redis and DynamoDB
• MLOps tooling , including Terraform, Docker, Airflow, MLFlow, Jenkins, GitHub Actions and Spacelift