Our vision Localization group is responsible for accurately localizing the vehicle on a high-definition 3D map with centimeter-level precision using surround camera systems to enable autonomous driving. Our work combines advanced geometric reasoning, scene understanding, and large-scale mapping to solve one of the core challenges of autonomous vehicles in complex real-world environments.
The role involves developing algorithmic and deep learning solutions that integrate mathematical optimization, computer vision, and 3D geometry. We work with modern neural network architectures including Transformers, GNNs, and CNNs to solve problems involving scene understanding, object association, and precise spatial reasoning in dynamic environments. The HD map contains rich geometric and semantic information that is critical for safe driving and cannot always be inferred reliably from images alone under all visibility conditions or viewpoints. In addition to achieving highly accurate localization, the team is also responsible for estimating map relevance and consistency with the current world state to ensure safe and reliable autonomous driving.
What will your job look like:
- Develop state-of-the-art localization algorithms for autonomous driving using multi-camera surround vision systems
- Design and implement deep learning models based on Transformers, Graph Neural Networks, and Convolutional Neural Networks
- Solve challenging problems involving 3D geometry, scene understanding, object matching, and spatial reasoning
- Combine learning-based methods with classical optimization and geometric algorithms
- Own the entire lifecycle from prototyping to deployment
- Analyze real-world driving data and improve system robustness under diverse environmental and visibility conditions
- Drive innovative solutions for high-precision localization at production scale
All you need is:
- 5+ years of practical experience developing computer vision or machine learning solutions using Python and frameworks such as PyTorch or TensorFlow – must
- B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with strong academic performance
- Solid foundation in algorithms, data structures, and computer vision/deep learning fundamentals
- Strong analytical skills, a sense of ownership, and the ability to work collaboratively
Skills Required
- 5+ years practical experience developing computer vision or machine learning solutions using Python and frameworks such as PyTorch or TensorFlow
- B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or related field
- Solid foundation in algorithms, data structures, and computer vision/deep learning fundamentals
- Experience designing and implementing deep learning models (Transformers, GNNs, CNNs) and combining learning with classical geometric optimization
- Strong analytical skills, ownership mentality, and ability to work collaboratively
What We Do
Mobileye is leading the mobility revolution with its autonomous-driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, machine learning, mapping, and data analysis. Founded in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and the RSS™ safety model. These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. Mobileye technology is used in over 170 million vehicles worldwide. In 2022, Mobileye became an independent company while still being majority-owned by Intel. Mobileye’s headquarters and R&D center are based in Jerusalem, with additional offices across Israel and around the world.
Why Work With Us
Our technology enables self-driving vehicles and mobility solutions, powers industry-leading advanced driver assistance systems, and delivers valuable intelligence to optimize mobility infrastructure.
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