Senior Applied Scientist - ADAS

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

Job summary

TomTom is expanding its ADAS Online team to advance state-of-the-art machine learning for scene understanding and environmental awareness. The Senior Applied Scientist will set the algorithmic direction for the in-vehicle spatial awareness stack and stay hands-on in model design and evaluation.

Requires 7+ years in ML, vision transformers, diffusion, or computer vision with strong PyTorch expertise. Mentorship and technical leadership are key parts of the role at TomTom Amsterdam.

Qualifications

• 7+ years of experience in machine learning, vision transformers, diffusion, or computer vision.
• Strong PyTorch expertise and hands-on model development.
• Experience designing and evaluating 3D perception and planning systems.

Responsibilities

• Define and drive the technical direction for physical AI algorithms.
• Define and execute a technical roadmap towards state-of-the-art reinforcement learning with physical AI world models.
• Design, implement, and improve ML/vision transformer models for 3D awareness and planning.
• Architect multi-modal fusion (camera, LiDAR, RADAR) to build 3D environments.
• Identify opportunities for larger end-to-end models to replace traditional approaches.
• Apply advanced ML techniques to improve perception performance.
• Lead experiments and benchmarking to deliver measurable gains in accuracy and robustness.
• Translate research ideas into scalable ML solutions.
• Provide technical guidance and mentorship to perception engineers.

Skills

Machine Learning

Vision Transformers

Diffusion

Computer Vision

Deep Learning

Optimization

Probabilistic Modeling

Reinforcement Learning

Gaussian Splatting

Object Detection

Multi-Object Tracking

Semantic Segmentation

Occupancy Modeling

Multi-Modal Fusion

Tools

PyTorch

Unity

Foundation Models

Job description

TomTom is 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 Senior Applied Scientist - ADAS, you will drive the algorithmic direction of the in-vehicle spatial awareness stack while remaining deeply hands-on in model design, experimentation, and performance improvement. Requires 7+ years of experience in machine learning, vision transformers, diffusion, or computer vision, with strong PyTorch expertise.

Technical (Must-have)

• Machine Learning
• Vision Transformers
• Diffusion
• Computer Vision
• Deep Learning
• PyTorch
• Optimization
• Probabilistic Modeling
• Reinforcement Learning
• Gaussian Splatting
• Object Detection
• Multi-Object Tracking
• Semantic Segmentation
• Occupancy Modeling
• Multi-Modal Fusion

Soft Skills

• Mentorship
• Technical Leadership
• Communication
• Collaboration

Technical (Nice-to-have)

• Autonomous Systems
• Robotics Perception
• 3D Data Representations
• Point Clouds
• BEV
• Voxel Grids
• Unity
• Foundation Models
• Large-Scale Training

Key Responsibilities

• 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
• Architect multi-modal fusion approaches (camera, LiDAR, RADAR) to build 3D environments
• 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

Machine Learning, Vision Transformers, Diffusion, Computer Vision, Deep Learning, PyTorch, Optimization, Probabilistic Modeling, Reinforcement Learning, Gaussian Splatting, Object Detection, Multi-Object Tracking, Semantic Segmentation, Occupancy Modeling, Multi-Modal Fusion, 7 years of relevant experience