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Required Algorithm Developer - Object Modeling Group
About the team:
The Object Modeling group is responsible for delivering real-world 3D object perception for autonomous driving and advanced driver-assistance systems.
In this role, you will solve real-world perception challenges in our core projects, using the companys innovative technologies across a wide range of sensors, including Computer Vision, LiDAR, Radar, and Imaging Radar.
You will combine classic programming with advanced algorithm development in C++ and Python, taking responsibility for both maintaining existing products and developing new features. As an Algorithm Developer, you will continuously learn and design new algorithms to address emerging problems and evolving challenges.
Work in our Algorithms department is dynamic and hands-on, covering the full lifecycle - from early-stage research and experimentation to bringing robust, high-impact solutions into production - while collaborating closely with other teams across.
This role requires working at our Jerusalem offices 2 days per week.
What will your job look like:
Your job will include a combination of classic programming and algorithm development
You will develop in both C++ and Python
You will need to both maintain the product and develop new features
Finally, you will need to learn and develop new algorithms which can address new problems as they arise.

Required AI Algorithm Engineer - Vision Localization Group
About the team:
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.

The Product Validation department is looking for a Validation Engineer.
Our department is responsible for delivering high-quality ADAS (Advanced Driver Assistance Systems) products.
We are the first line of support for our customers around the globe, and as our Validation Engineer, you will interact with most of our departments to achieve our goals.
What will your job look like:
Perform system-level validation of embedded systems, covering both hardware and software, with a strong focus on functional testing
Design and maintain test environments, including lab setups, test systems, and configurations.
Write and execute test plans and test cases based on system requirements, including manual and automated tests.
Validate communication protocols and system interfaces, and perform hardware bring-up and integration testing.
Install and support debug systems and sensors on development vehicles and assist automotive customers during integration.

Product Validation department is looking for a Validation Engineer Team Lead.
Our department is responsible for delivering high-quality ADAS (Advanced Driver Assistance Systems) products. We are responsible for integration and validation of our products on customer systems. And as our Validation Engineer Team Lead you will be interacting with most of our departments, to achieve our goals.
What will your job look like?
Lead and guide a team of system validation engineers.
Work closely with the different Project managers to drive and ensure proper validation plan
Work closely with R&D teams across In order to establish a proper test plan and to achieve fast Root-Cause of issues that arise during the system testing phase
Test and evaluate the system functionality & performance in both hardware and software aspects.
Drive test development and integration methods, to ensure high-quality products.
Executing Manual tests as well as built-in automated test sets (Hands-on).

We are looking for an Electro-Optical Engineer to join the development team and lead hands-on research, characterization, testing, and integration of advanced electro-optical technologies into complex multidisciplinary systems.
The role combines practical lab work, system-level design, execution, and technological innovation. Role includes leading design and implementation of sensors, lenses, cameras, thermal systems, optical measurement, image quality, sensor accuracy, and integration with broader platform technologies.
As part of the LYNX team, the engineer will support component-level and system-level design, experimentation, integration, supplier technical discussions, test planning, documentation, and collaboration with mechanical, electronics, software, system engineering, and validation teams.
Responsibilities:
Characterize, evaluate, and integrate electro-optical components suh as sensors, lenses, cameras, compasses, thermal imaging modules, and related optical subsystems.
Plan, develop, and execute component-level and system-level experiments, including optical bench testing, optical measurements, and system integration activities.
Define and implement optical test methodologies for image quality, sensor accuracy, optical performance, environmental behavior, and system-level functionality.
Support the integration of new technologies into existing LYNX systems and future developments, including interfaces with IMU, GPS, laser range finders, compass modules, and additional platform sensors.
Work with suppliers and subcontractors on requirements definition, design reviews, performance evaluation, technical trade-offs, and issue resolution.
Write technical specifications, test plans, experiment reports, analysis summaries, and supporting engineering documentation and transfer to production processes.
Support system integration, troubleshooting, verification, validation, and field-testing activities.
Collaborate closely with multidisciplinary teams, including mechanics, electronics, software, system engineering, QA, and operations.

We are looking for a Computational Biologist to focus on Computational antibody design, playing a central role in the design and optimization of our therapeutics antibodies, while also conducting multi-omics analysis tasks within the group.

Responsibilities :

You will: Work closely with our computational biologists multidisciplinary team and with the Antibody discovery functional unit
Drive computational antibody design, applying state-of-the-art computational and AI models to design and optimize multispecific therapeutics antibodies
Translate engineering concepts into experimentally validated candidates
Act as a scientific liaison with external CROs on antibody design and optimization projects as needed
Explore new methods that expand our computational antibody design capabilities, including making effective use of AI/ML-based tools
Conduct end-to-end broader computational analyses including multi-omics datasets for target analysis, as needed
Communicate scientific results and design rationale clearly to internal and external audiences