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Algorithm team lead We are looking for an experienced Algorithm team lead to drive the development of advanced computer vision and 3D algorithms, from concept through deployment on edge systems.

we are a global leader in autonomous driving technologies and advanced driver-assistance systems (adas). our cutting-edge solutions, including the eyeq chip, mobileye supervision, mobileye drive, and mobileye chauffeur, leverage computer vision and Machine Learning to enhance vehicle safety and enable self-driving capabilities. integrated into millions of vehicles worldwide, our technology is redefining the automotive industry and driving the evolution towards smarter, safer, and more autonomous mobility.
in our group, we research, develop, and deploy state-of-the-art lidar based techniques to achieve world-class results, enabling the safe development of autonomous driving features and advanced driver assistance systems. what will your job look like:
research, design, develop, and implement lidar based algorithms in both Python and C ++ for solving complex problems
evaluate existing models and techniques, and propose innovative approaches to improve algorithm performance and accuracy
examine your algorithms on large-scale real-world data from our data collection vehicles across the globe
collaborate with cross-functional teams to understand requirements and develop solutions
optimize existing algorithms to improve performance and scalability

join our rem (road experience management) department - the team driving the automatic creation of high-definition maps, a cornerstone technology behind our autonomous driving and advanced driver-assistance systems. rem map creation leverages cutting-edge algorithms executed at massive scale using Big Data technologies, requiring both a deep understanding of the map creation pipeline and strong technical expertise. you will be part of our priority semantics algorithmic team, focused on understanding right-of-way rules and interactions derived from traffic signs, road structures, and driving behavior.
the team uses cutting-edge technologies, including graph neural networks (gnns) and data -driven learning techniques, to model complex driving scenarios and extract meaningful insights from large-scale real-world driving data.
this role requires a deep understanding of the data itself, modeling complex semantics, and extracting insights using learning-based approaches to accurately represent real-world driving priorities.
what will your job look like?
design, train, and evaluate cutting-edge deep learning models on rem proprietary map data
perform high-scale, large-volume data analysis
integrate new map-based algorithms with full ownership
develop tools that enable fast and effective data introspection
optimize models and results where needed.