Senior Applied Scientist

About the role

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. What you will do: 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. What you will need: 4+ years of professional experience in Applied Science, Machine Learning, algorithm development, computer vision or related field. Bachelor’s degree or higher in Computer Science, Machine Learning, Computer Vision, Geospatial Science, Statistics or another quantitative field. Master’s or PhD is a plus. Strong fundamentals in algorithms and machine learning, including model development, evaluation, statistics and experimental design. Proficiency in Python, an ML framework such as PyTorch or TensorFlow, and large-scale data processing tools such as Spark or Databricks. Experience taking algorithms, ML models or data pipelines from experimentation into production. Experience leading well-scoped technical projects and mentoring junior colleagues. Ability to work across data, algorithms, modeling, ground truth and evaluation rather than operating within only one area of expertise. Strong problem-solving skills and the ability to independently approach complex and ambiguous problems. Proficient written and verbal communication skills in English. You already live in the Netherlands. We cannot offer relocation for this role. What we offer A competitive compensation package, of course. Time and resources to grow and develop, including a personal development budget and paid leave for learning days, as well as paid access to e-learning resources such as O’Reilly and LinkedIn Learning. Time to support life outside of work, with enhanced parental leave plus paid leave to care for loved ones and volunteer in local communities. Work flexibility, where TomTom’ers, in agreement with their manager and team, use both the office and home to focus, collaborate, learn and socialize. It’s all about getting the best out of both worlds – we ask TomTom’ers to come to the office two days a week, and the remaining three are free to be worked in either location. Improve your home office with a setup budget and get extra support with a monthly allowance. Enjoy options to work from your home country a

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