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TomTom is seeking an Applied Scientist to advance the Orbis Road and Lane Models by transforming massive geospatial data into high-quality map content. You will develop ML pipelines for navigation-related data and collaborate with cross-functional teams to productionize research.
With 5+ years in industry, you’ll use Java and Python, contribute to large data streams, and help deliver our maps at scale across devices, teams, and partners worldwide.
At TomTom, the Maps team sits at the heart of our vision to build the world's mostaccurate, fresh, and intelligent map. As an Applied Scientist, you will help evolve the Orbis Road Model Map and the Orbis Lane Model Map by transforminghigh‑fidelity,high‑volumedata into map content that powersnext‑generationnavigation, automated driving, andhigh‑qualityGuidance for millions of drivers.
You willtplay a pivotal role in building navigation-related map content from a collection of massive geospatial data sources using ML algorithms and solutions.— fueling products and partnerships that rely on TomTom's map as a competitive differentiator, from global OEMs tocutting‑edgeautomated driving programs.
Design and develop algorithms that extract actionable insights from massive, imperfect datasets, turning rawgeospatialdata into intelligence that powers the future ofmap-makingtechnology.
Work with one of the largest traffic data streams worldwide, applying yourexpertiseto decode complex datasets and improve mobility systems.
Take ownership of the full lifecycle of software projects, ensuring smooth transitions from research to production-level implementation.
Support and improve production environments to guarantee operational excellence of the systems you build.
Work closely with Software Engineers and Product Managerson the team.
Auniversity-leveldegree inMachine Learning,Computer Science,or a relevant field.
5+ years of industry experience developing production-grade code, withproficiencyin Java and Python.
Proventrack recordin solving business problems through ML solutions(e.g.Computer Vision, classic ML algorithms,etc.)
Strong skills in Software Engineering, both in greenfield projects andoptimizingexisting systems.
You’rea collaborative team player who thrives in an international environment, and you have strong written and verbal communication skills in English.
Experience in handling large volumes of Geospatial data
Familiarity with DevOps practices and cloud platforms like Azure.
Familiarity withBig Data pipelines (e.g.Spark/Kafka)
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.
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.
Our recruitment team will work hard to give you a meaningful experience throughout your journey with us, no matter the outcome. Your application will be screened closely and you can rest assured that all follow-up actions will be thorough, from assessments and interviews all the way through onboarding. To find out more about our hiring FAQs.
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.