Meet the team  

You’ll join the Traffic Control Features team within TomTom’s Automated Driving organization. The team builds the technology that turns real-world observations into reliable map information about traffic signs, traffic lights, stop lines and road markings. 

You’ll work with applied scientists and software engineers to develop algorithms and machine-learning solutions that detect, position and connect these features to the right roads and driving directions. The goal is to deliver accurate, scalable map content that supports navigation and advanced driving experiences. TomTom measures these features using quality dimensions such as recall, precision, and road-relation accuracy. 

Develop algorithms and ML solutions for traffic signs, traffic lights, road markings, and other traffic-control features, including projects with Computer Vision and Image Recognition. Design and productionize solutions that extract reliable map information from diverse, large-scale and noisy real-world data sources, including car sensor data and unstructured information. Improve how features are detected, positioned, and associated with the correct road/lane and driving direction. Drive measurable improvements in recall, precision, and overall map quality against customer-facing targets. Own components of production pipelines, from input data and feature extraction through evaluation and validated map output. Solve complex problems involving geospatial geometry, map matching, computer vision, image recognition, noisy observations, ground-truth quality, and large-scale evaluation. Run experiments, translate successful approaches into production solutions, and clearly document outcomes. Use AI tools, such as Claude Code, to support problem solving, data analysis, implementation, and engineering productivity. Mentor junior colleagues, provide insightful code reviews, and contribute to hiring.