Algorithm Engineer jobs in Ramat Gan

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: • B.Sc. in Computer Science, Software Engineering, or a related field from a leading university with a proven record of excellence. • M.Sc. with a research thesis is an advantage. • Strong programming skills in Python and C++. • Solid foundation in algorithms, data structures, mathematics, and computer vision or deep learning fundamentals. • Strong analytical skills, a high level of ownership, and the ability to work effectively in a collaborative environment. 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!

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: • 2+ 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. 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!

We are Object Perception group at Mobileye, developing deep learning–based perception systems for autonomous driving. Our work spans scene understanding, multi-camera reasoning, 3D modeling, and behavior prediction. We are looking for a senior computer vision engineer: a hands on individual contributor whose work will be broad and touch many projects across the group, to lead long-term research initiatives and POCs that shape the technical direction of our technology. What will your job look like: • Lead long-term applied research and POCs that determine the direction of our perception and autonomy technology. • Design and implement modern end-to-end perception and multi-modal learning systems across diverse vision tasks (e.g., detection and tracking, 3D reconstruction, multi-camera fusion, motion prediction). • Translate research innovations into high-quality, validated POCs designed for adoption by production teams and deployment within autonomous vehicle platforms. All you need is: • M.Sc. in Mathematics, Computer Science, Electrical Engineering, or related field (PhD - an advantage). • 8+ years of hands-on experience developing computer vision and deep learning systems. • Proven experience driving vision models from research through POC and into production. • Able to take a vaguely-defined research direction and own it end-to-end, independently. • Strong programming skills in Python. Nice to have: • Broad hands-on experience across vision tasks such as object detection and tracking, and 3D scene understanding. • Technical leadership experience (team management experience an advantage). • Experience in motion prediction, trajectory forecasting, behavior modeling, or learning-based navigation for autonomous systems. • First-authored publications at leading peer-reviewed conferences (e.g., CVPR, ECCV, ICCV, NeurIPS, ICML, ICLR). 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!

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. 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!

We are looking for a Senior ML Algorithm Engineer to lead the development and optimization of machine learning models for challenging real-world problems. In this role, you will work hands-on across the full model-development lifecycle: understanding the task, designing and adapting algorithms, building effective training strategies, analyzing data and failure modes, and improving model quality and efficiency through rigorous experimentation. This is an algorithm-focused role for someone who enjoys getting deeply involved in the details of model training and optimization. You will not simply operate an existing training infrastructure—you will investigate open-ended problems and develop practical solutions involving model architecture, data and sample selection, training objectives, optimization methods, and evaluation What will your job look like: • Work on the semantics of road objects, using harvested tabular data as the primary input to our algorithms — turning large-scale, real-world observations into models that capture object meaning, attributes, and behavior on the road network. • Design, implement, and optimize machine learning and deep learning algorithms for these semantic tasks, from architecture and training objectives through evaluation and efficiency. • Develop and improve end-to-end model training pipelines, from data preparation and sampling of harvested tabular datasets through training and evaluation. • Investigate model behavior, identify failure modes, and drive targeted algorithmic improvements. • Develop effective strategies for data selection, dataset composition, sampling, augmentation, loss design, and training schedules. • Lead the investigation of complex algorithmic challenges, uncover patterns in data and model behavior, and translate insights into measurable improvements. All you need is: • 5+ years of experience in algorithm engineering using machine learning, deep learning, or neural networks. • Strong hands-on experience designing, training, evaluating, and optimizing. • Strong programming skills in Python. • Hands on experience with Spark, Pandas, Pytorch and AWS. • Experience with Polars and DuckDB- an advantage • Experience with some of the following: sampling strategies, data augmentation, hyperparameter optimization • Strong understanding of distributed systems, scalability, and performance optimization. • Ability to independently investigate complex problems, identify patterns in data and model behavior, run experiments, and translate findings into measurable algorithmic improvements. • Strong analytical and problem-solving skills, with a practical, hands-on, and ownership-driven mindset. 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!

We are Object Perception group at Mobileye, developing deep learning–based perception systems for autonomous driving. Our work spans scene understanding, multi-camera reasoning, 3D modeling, and behavior prediction. We are looking for a senior computer vision engineer: a hands on individual contributor whose work will be broad and touch many projects across the group, to lead long-term research initiatives and POCs that shape the technical direction of our technology. What will your job look like: • Lead long-term applied research and POCs that determine the direction of our perception and autonomy technology. • Design and implement modern end-to-end perception and multi-modal learning systems across diverse vision tasks (e.g., detection and tracking, 3D reconstruction, multi-camera fusion, motion prediction). • Translate research innovations into high-quality, validated POCs designed for adoption by production teams and deployment within autonomous vehicle platforms. All you need is: • M.Sc. in Mathematics, Computer Science, Electrical Engineering, or related field (PhD - an advantage). • 4+ years of hands-on experience developing computer vision and deep learning systems. • Proven experience driving vision models from research through POC and into production. • Able to take a vaguely-defined research direction and own it end-to-end, independently. • Strong programming skills in Python. Nice to have: • Broad hands-on experience across vision tasks such as object detection and tracking, and 3D scene understanding. • Technical leadership experience (team management experience an advantage). • Experience in motion prediction, trajectory forecasting, behavior modeling, or learning-based navigation for autonomous systems. • First-authored publications at leading peer-reviewed conferences (e.g., CVPR, ECCV, ICCV, NeurIPS, ICML, ICLR). 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!