Senior Applied Scientist - ADAS

TomTom; Amsterdam; Hybrid; EUR 150,000 - 210,000; Full time

Benefits offered by this job

Development budget

Learning days & resources

Parental leave

Hybrid work model

Home office allowance

Global mobility opportunities

Annual hackathons & events

Inclusive culture

Job summary

TomTom is seeking an ML Staff Engineer to lead the algorithmic direction of our ADAS/ADS spatial awareness stack. You will stay hands-on in model design and experimentation, mentor a small high-velocity team, and drive the roadmap for 3D perception and multi-modal fusion using state-of-the-art transformer-based architectures.

You will shape scalable ML solutions, advance 3D map data processing, and collaborate with cross-functional experts to deliver robust perception systems for automotive

Qualifications

• 7+ years of experience in machine learning, vision transformers, diffusion, or computer vision.
• Deep expertise in modern deep learning architectures.
• Strong hands-on experience with PyTorch (or equivalent frameworks).
• Proven experience building and iterating on large-scale ML models.
• Strong mathematical foundations in optimization and probabilistic modeling.

Responsibilities

• Define and drive the technical direction for physical AI algorithms.
• Define and execute a roadmap towards state-of-the-art world models using physical AI.
• Design, implement, and improve ML/vision transformer models for 3D awareness and planning.
• Architect multi-modal fusion approaches (camera, LiDAR, RADAR) for 3D environments.
• Lead structured experimentation and benchmarking to deliver measurable gains in accuracy and robustness.
• Translate research ideas into reliable, scalable ML solutions.
• Provide technical guidance and mentorship to perception engineers.

Skills

ML systems

Vision transformers

Diffusion

PyTorch

Large-scale models

Probabilistic modeling

Optimization

Tools

PyTorch

Unity

Job description

We are building a high-performance ADAS Online team focused on advancing state-of-the-art machine learning and AI algorithms for scene understanding and environmental awareness. As ML Staff Engineer, you will drive the algorithmic direction of our present and future in-vehicle spatial awareness stack while remaining deeply hands-on in model design, experimentation, and performance improvement. You will contribute as a senior technical authority and mentor within a small, high-velocity team.

This spatial awareness stack will leverage modern transformer and end-to-end architectures to transform vehicle sensor data along with real-time 3D map data from the cloud into a 3D, semantically defined environment identifying all static and dynamic objects. This is a high-ownership technical role in a fast-moving, data-driven AI environment.

What You'll Do

• Define and drive the technical direction for physical AI algorithms
• Define and execute on a technical roadmap towards state-of-the-art reinforcement learning using physical AI world models.
• Design, implement, and improve ML / vision transformer models for 3D awareness and planning. These include Gaussian Splatting (3DGS), Diffusion, object detection, multi-object tracking, semantic segmentation, and occupancy modeling
• Architect multi-modal fusion approaches (camera, LiDAR, RADAR) to build 3D environments
• Per the roadmap, identify where larger end-to-end models should replace more traditional approaches
• Apply advanced ML techniques (Transformers, representation learning, large-scale models) to improve perception performance
• Lead structured experimentation and benchmarking to deliver measurable gains in accuracy and robustness
• Translate research ideas into reliable, scalable ML solutions
• Provide technical guidance and mentorship to perception engineers

What You'll Need

• 7+ years of experience in machine learning, vision transformers, diffusion, or computer vision
• Deep expertise in modern deep learning architectures
• Strong hands-on experience with PyTorch (or equivalent frameworks)
• Proven experience building and iterating on large-scale ML models
• Strong mathematical foundations in optimization and probabilistic modeling
• Track record of delivering measurable improvements in ML system performance
• Experience guiding technical decisions within a small engineering tea

Nice to Have

• Experience in autonomous systems or robotics perception
• Publications or patents in machine learning or perception
• Experience with 3D data representations (gaussian spatting, point clouds, BEV, voxel grids) and 3D engines like Unity
• Familiarity with large-scale training or foundation models
• Experience mentoring engineers in advanced ML topics

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 are the ADAS & ADS Product Unit, leading the production of TomTom’s HD maps and ADAS technology.

In a diverse team of applied scientists, engineers, data scientists, and more, equipped with a broad array of expertise, you’ll collaborate on groundbreaking location-based technologies and applications.

More specifically, you’ll be at the forefront of the creation of advanced HD maps. You’ll also help update these in real-time, ensuring our maps are pushing the world forward instantly. These maps will then go on to empower the largest car manufacturers, transportation giants, and major tech companies around the world.

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.