Machine Learning Staff Engineer – ADAS Online

TomTom; Amsterdam; On-site; EUR 75,000 - 95,000; Full time

Benefits offered by this job

Competitive compensation

Personal development budget

Paid leave for learning days

Hybrid work model

Home office setup budget

Extra day off for birthday

Job summary

Join TomTom in Amsterdam as a Machine Learning Staff Engineer focused on cutting-edge technologies for HD maps and ADAS systems. This role involves defining technical direction for AI algorithms, enhancing reinforcement learning techniques, and mentoring engineers.

Applicants should have extensive experience in machine learning and computer vision, particularly in building large-scale models. The position promotes work-life balance with hybrid flexibility, development budgets, and competitive compensation.

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.

Responsibilities

• Define and drive the technical direction for physical AI algorithms.
• Design, implement, and improve ML/vision transformer models.
• Lead structured experimentation and benchmarking.

Skills

Machine learning

Computer vision

Vision transformers

Deep learning architectures

Optimization

Probabilistic modeling

PyTorch

Job description

Join TomTom’s Maps ADAS & ADS team in Amsterdam as a Machine Learning Staff Engineer focused on ADAS Online.

This role sits within the ADAS & ADS Product Unit, which leads the production of TomTom’s HD maps and ADAS technology. You will collaborate with applied scientists, engineers, data scientists, and other specialists on advanced location-based technologies, including the creation and real-time updating of HD maps used by major car manufacturers, transportation companies, and technology businesses worldwide.

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, including Gaussian Splatting (3DGS), diffusion, object detection, multi-object tracking, semantic segmentation, and occupancy modeling
• Architect multi-modal fusion approaches using camera, LiDAR, and RADAR to build 3D environments
• Identify, based on the roadmap, where larger end-to-end models should replace more traditional approaches
• Apply advanced ML techniques such as transformers, representation learning, and 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 team

What's Nice to Have

• Experience in autonomous systems or robotics perception
• Publications or patents in machine learning or perception
• Experience with 3D data representations such as 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.

Time and resources to grow and develop, including a personal development budget, paid leave for learning days, and 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, with a hybrid approach that combines office and home working. TomTom’ers are asked to come to the office two days a week, while the remaining three days can be worked in either location.

A home office setup budget and extra support through a monthly allowance.

Options to work from your home country and abroad for a set number of days each year.

A competitive holiday plan, plus an extra day off to celebrate your birthday.

Annual events like Hackathon and DevDays to bring ideas to life with teammates from around the world.

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.

About TomTom

You’ll help people find their way in the world by contributing to TomTom’s ambition to engineer a real‑time map.