Senior Applied Scientist Engineering Maps Directions(Maps) Amsterdam, The Netherlands

TomTom; Amsterdam; Hybrid; EUR 120,000 - 180,000; Full time

Benefits offered by this job

Dev budget

Learning days

Parental leave

Hybrid work

Home office budget

Job summary

TomTom’s Traffic Control Features team in the Automated Driving organization seeks an experienced Applied Scientist/ML Engineer to develop ML solutions for traffic-control features and productionize pipelines that scale from car sensor data to map outputs.

You will work with scientists and engineers, mentor juniors, and help hire while improving recall, precision and map quality. Hybrid work with two days in-office in the Netherlands.

Qualifications

• 4+ years of professional experience in Applied Science, ML, algorithm development, computer vision or related field.
• Bachelor’s degree or higher in Computer Science, ML, CV, Geospatial Science, Statistics or related field. Master’s/PhD is a plus.
• Strong fundamentals in algorithms and ML, including model development, evaluation, statistics and experimental design.
• Proficiency in Python and ML frameworks (PyTorch or TensorFlow); experience with large-scale data processing (Spark/Databricks).
• Experience taking algorithms, ML models or data pipelines from experimentation into production.
• Experience leading technical projects and mentoring junior colleagues.
• Proficient written and verbal English communication.
• You already live in the Netherlands; relocation not offered.

Responsibilities

• Develop algorithms and ML solutions for traffic signs, lights, road markings and other traffic-control features.
• Design and productionize solutions to extract map information from large-scale, noisy real-world data.
• Improve detection, positioning and association with correct road and driving direction.
• Run experiments and translate results into production solutions with clear documentation.
• Mentor junior colleagues and provide code reviews; contribute to hiring.

Skills

Algorithms

Machine Learning

Python

English

Mentoring

Education

Bachelor's degree

Master's/PhD a plus

Tools

PyTorch

TensorFlow

Spark

Databricks

Job description

Meet the teamYou’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 and abroad for a set number of days each year, to visit family and friends, or to simply explore the world we’re mapping.

Take the holidays you want with a competitive holiday plan, plus an extra day off to celebrate your birthday.

Join annual events like our Hackathon and DevDays to bring your ideas to life with talented teammates from around the world.

Become a part of our inclusive global culture and have the chance to collaborate with a diverse community – we have over 80 nationalities at TomTom!

Find out more about our global benefits and enjoy additional local benefits tailored to your location.

Meet your team

We’re Maps, a global team within TomTom’s Location Technology Products technical unit. Our team is driven to deliver the most up-to-date, accurate and detailed maps for hundreds of millions of users around the world. Joining our team, you’ll continuously innovate our mapmaking processes, directly contributing to our vision: engineering the world's most trusted and useful map.

At TomTom...

You’ll help people find their way in the world. In 2004, TomTom revolutionized how the world moves with the introduction of the first portable navigation device. Now, we intend to do it again by engineering the first-ever real-time map, the smartest and most useful map on the planet.

Work with a team of 3,300+ unique, curious and passionate problem-solvers. Together, we’ll open up a world of possibilities for car manufacturers, enterprises and developers to help people understand and get closer to the world around them.

TomTom is an equal opportunity employer

TomTom is where you can find your place in the world. Every day we welcome, nurture and celebrate differences. Why? Because your uniqueness is what makes you, you. No matter your culture or background, you’ll find your impact at TomTom.Research also shows that sometimes women and underrepresented communities can be hesitant to apply for positions unless they believe they meet 100% of the criteria. If you can relate to this, please know that we’d love to hear from you.

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