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Amsterdam
29 May 2026
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Applied Scientist

TomTom

Amsterdam
29 May 2026
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Applied Scientist

Join TomTom's ADAS & ADS Product Unit as an Applied Scientist on the ALF team, developing HD maps and ML systems for real-time localization. You will design algorithms, build ML pipelines, and improve quality metrics in a collaborative on-site role in Amsterdam. Requires 3+ years experience, Python proficiency, and ML/algorithm fundamentals.

AIHybridFull-timeMid LevelPythonPyTorch

Applied Scientist

Join TomTom's ADAS & ADS Product Unit as an Applied Scientist on the ALF team, developing HD maps and ML systems for real-time localization. You will design algorithms, build ML pipelines, and improve quality metrics in a collaborative on-site role in Amsterdam. Requires 3+ years experience, Python proficiency, and ML/algorithm fundamentals.

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AIHybridFull-timeMid LevelPython

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site: 2 days per week in office, 3 days remote (flexible)

Experience Required

3 years

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)
PythonPyTorchTensorFlowApache SparkDatabricksMachine LearningAlgorithm DesignData StructuresStatisticsExperimental DesignComputer VisionGeospatial ScienceSignal ProcessingMLOpsAgile Methodologies
Soft Skills
CuriosityDesire to learnProblem-solvingCommunicationTeamworkAdaptabilityMentoring

Preferred Qualifications

Technical (Nice-to-have)
Master's degreePhDClassical MLClusteringComputer Vision (detection, segmentation)Polygon geometryMap-matchingSpatial indexingTraining Pipelines

Key Responsibilities

  • •Develop high-quality algorithms and ML software for TomTom's HD maps for ADAS.
  • •Contribute to design, implementation, and integration of algorithms, ML systems, and data pipelines.
  • •Contribute to measurable improvements in output quality (recall, precision, latency, cost).
  • •Own well-scoped components within processing pipelines from input to validated outputs.
  • •Tackle complex technical problems at scale with noisy upstream signals and geospatial geometry.
  • •Build iteratively using agile methodologies and rigorous experimentation; document outcomes.
  • •Support junior engineers and interns, and contribute to hiring as an interviewer.
Applied ScientistMachine LearningHD MapsADASPythonPyTorchTensorFlowApache SparkComputer VisionGeospatial
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