Are you ready to lead the next wave of advancements in autonomous driving?
At TomTom, we're on a mission to transform groundbreaking scientific advancements into real-world HD mapping solutions that power the future of autonomous vehicles.
As a Senior Applied Scientist specializing in Computer Vision, you'll be the driving force behind large-scale 3D reconstruction projects and develop advanced algorithms for real-time processing.
You'll work in a collaborative, fast-paced environment that values agility and real results, enabling you to lead from the front in solving complex mapping challenges.
Ready to make a real difference?
Let's get started!
What you'll do: Drive the development and optimization of Computer Vision models for autonomous driving applications, focusing on real-time, scalable solutions.
Enhance real-time systems for processing LiDAR and camera data, with a focus on geospatial accuracy and 3D mapping.
Architect and optimize scalable, high-performance ML/CV models tailored for autonomous driving applications.
Manage full project lifecycles, ensuring alignment with business goals and customer needs.
Fine-tune Computer Vision algorithms, balancing performance with business requirements.
Drive automation initiatives to streamline data processing and boost mapping efficiency.
Provide technical leadership, guiding complex discussions and facilitating team alignment.
Champion iterative methodologies, fostering a culture of continuous innovation.
Mentor junior engineers and scientists, contributing to a growth-oriented and collaborative team culture.
What you'll need: Educational background: PhD in Computer Vision, Machine Learning, or related fields with a focus on autonomous driving.
Professional experience: 5+ years in applied science roles, with expertise in delivering Computer Vision projects from concept to deployment.
Technical skills: Expertise in Python and Computer Vision libraries (e.G., OpenCV, PyTorch, TensorFlow).
Scalability & performance: Familiarity with large-scale systems and tools like Spark and Databricks.
Algorithm expertise: Profound understanding of data structures and algorithms to solve practical challenges.
Sensor & mapping knowledge: Hands-on experience with sensor data processing, sensor fusion, and mapping technologies (e.G., SLAM, HD mapping).
Communication skills: Ability to explain complex technical concepts to cross-functional teams effectively.
Tech stack familiarity: Working knowledge of Git, Docker, Kubernetes, and cloud platforms (e.G., Azure, AWS).
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.
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