Senior Applied Scientist — HD Maps & Real-Time ML for ADAS

TomTom; Amsterdam; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Personal development budget

Paid learning days

Office/home hybrid work (2 days in the

Home office setup budget

Birthday leave

Hackathon and DevDays participation

Job summary

TomTom is seeking a Senior Applied Scientist to join the ALF team in the ADAS & ADS Product Unit. You will help develop algorithms and ML software powering HD maps for ADAS, partner with engineers, and own feature quality trajectories toward ambitious product targets.

You will design, implement, and productionize ML systems and data pipelines, mentor engineers, and contribute to hiring. Strong Python and ML framework experience are essential, with a background in geospatial ML a plus.

Qualifications

• 4+ years in Applied Science, ML, or algorithm development.
• Bachelor's degree minimum in a quantitative field; advanced degrees a plus.

Responsibilities

• Develop high-quality algorithms and ML software for TomTom's HD maps for ADAS.
• Design and implement ML systems and data pipelines from framing to production rollout.
• Drive improvements in recall, precision, latency, and cost against customer targets.
• Lead projects and own components through upstream data to published outputs.

Skills

Python

ML frameworks

Spark/Databricks

English communication

Algorithm design

Geospatial/ ML data pipelines

Mentoring

Education

Bachelor's in CS/ML/Geospatial/Stats

Masters/PhD a plus

Tools

PyTorch

TensorFlow

Spark/Databricks

Job description

TomTom is seeking a Senior Applied Scientist to join the ALF team in the ADAS & ADS Product Unit. You will help develop algorithms and ML software powering HD maps for ADAS, partner with engineers, and own feature quality trajectories toward ambitious product targets.

You will design, implement, and productionize ML systems and data pipelines, mentor engineers, and contribute to hiring. Strong Python and ML framework experience are essential, with a background in geospatial ML a plus.