Overview
The road algorithm team is responsible for the critical and challenging task of detecting the drivable lanes on the road. We focus on Deep Learning algorithms, classical Computer Vision and Geometric Modeling algorithms. We are looking for an Algorithm Developer to help us advance our technology and push the boundaries of what's possible in autonomous driving.
Full job description
About The Role
The road algorithm team is responsible for the critical and challenging task of detecting the drivable lanes on the road. We focus on Deep Learning algorithms, classical Computer Vision and Geometric Modeling algorithms. We are looking for an Algorithm Developer to help us advance our technology and push the boundaries of what's possible in autonomous driving.
What Will Your Job Look Like:
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Develop and optimize computer vision and deep learning algorithms to accelerate data generation and labeling workflows for autonomous driving
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Apply both classical computer vision techniques and modern deep learning methods to solve large-scale data challenges
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Collaborate closely with development and annotation teams to enhance automation and ensure high-quality data
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Own the entire lifecycle from prototyping to scalable deployment within internal pipelines and tools
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Develop tools to evaluate and analyze algorithm performance, robustness, and operational efficiency
All You Need Is:
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B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with strong academic performance
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Solid foundation in algorithms, data structures, and computer vision/deep learning fundamentals
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Practical experience developing computer vision or machine learning solutions using Python and frameworks such as PyTorch or TensorFlow – must
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Strong analytical skills, a sense of ownership, and the ability to work collaboratively
Additional information
Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!
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