לוח משרות דרושים מדעים מדוייקים ברמת גן, לחיפוש זה נמצאו 46 משרות

Our Unit Level Verification Team is looking for an experienced verification engineer to be involved in the development of our future AI and deep learning HW accelerators.
This is an exciting opportunity to join a team of highly talented engineers, working on the most cutting-edge technologies to deliver our EyeQ future chips, aimed to power the worlds first fully Autonomous Vehicle!
What will your job look like:
Define, implement and enhance verification environments using UVM methodology.
Write and debug tests that combine UVM methodology and SW code.
Identify and write various types of coverage measures.
Collaborate with designers, architects, and SW developers from Haifa and Jerusalem teams to deliver the most comprehensive verification environment.
Integrate Industry Standard (such as AXI and OCP) and other 3rd party VIPs.

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.

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.

Outstanding Graduate Algorithm Developer - 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.

Required Experienced SoC Verification Engineer
About the team:
Our SOC verification group owns the important and challenging job of verifying our chip. It is involved from product specification to final SOC delivery, and involves all the system components. The group is made up of few of the best verification engineers, so besides contributing to making our roads safer, youll get the chance to work at one of the most professional verification teams.
What will your job look like:
You'll be responsible for Pre-Silicon system-level verification of the most cutting-edge AI accelerators and technologies in the automotive field.
Define the TestPlan, develop and run tests on simulation/emulation environments, develop test environment and verification collaterals.
You'll have a broad effect on our unique product from the very beginning of the process.

Required Experienced Deep Learning Software Engineer - Algorithms & Data
About the team:
Our team develops models for road perception. We turn multi-sensor inputs (vision, maps, and more) into models that understand road geometry and behavior. We work at the intersection of algorithms, DL models, infrastructure, and data engineering.
what will your job look like?
Own road data pipelines end to end: tools for datasets and databases, running across S3 and on-prem
Design algorithms on large-scale vision and multi-sensor data (maps, sporadic inputs), including geometric reasoning from 2D image space to 3D world space for perception and world modeling
Implement and develop algorithms for the AV production system
Build evaluation tools, algorithms, metrics, and related infrastructures.

We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges - from object detection and scene understanding to 3D perception - using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
Develop and train neural networks for complex perception tasks in real-world driving environments.
Design and analyze deep learning pipelines, from data to deployment.
Collaborate with algorithm, software, and data experts to deliver production-ready models.
Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.

Required Experienced Deep Learning Algorithm Developer
About the team:
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:
Research and develop state-of-the-art computer vision and deep learning algorithms for ADAS and autonomous driving.
Participate in the entire development cycle, from initial research and prototyping to deployment on real-time embedded systems within the vehicle.
Collaborate with engineering and research teams in Computer Vision, Machine Learning, and Data Engineering to solve real-life problems.
Analyze large datasets to improve algorithm performance and robustness.

We are seeking a highly skilled and innovative Control Engineer to join our dynamic team dedicated to advancing the field of autonomous vehicles. As a Control Engineer, you will play a crucial role in designing, developing, implementing and testing hands on control algorithms to enhance the performance, safety, and efficiency of our autonomous vehicle systems.
Please note that this position requires 2 days a week at our HQ in Jerusalem.
What will your job look like:
Work on developing and optimizing control algorithms for the vehicle.
Run and analyze simulations to test autonomous vehicle in virtual environments.
Collaborate with hardware engineers to integrate control algorithms with the vehicle's hardware components, such as sensors, actuators, and onboard computers.
Working with communication protocols and interfaces for both internal and external communications with different components of the system.
Customer facing workshops to discuss and test your algorithms.
Testing your algorithms in an Autonomous vehicle.

Required Deep Learning Algorithm Engineer | Learned-Policy Group
About the team:
Build the intelligence behind the next driving decision.
Were developing learning-based driving policies for complex, real-world
scenarios. Were looking for an engineer who can turn model ideas into reliable
algorithms that run as part of our driving systems.
Youll work across model development, training, evaluation, and integration.
Youll analyze model behavior, improve the data and training process, and work
with other teams to validate performance in simulation and on real vehicles.
This is a high-impact role with direct influence on a core part of our
driving technology and its future products.
What will your job look like?
Develop and improve deep learning models for planning, decision making, and driving behavior.
Work across the full development cycle, from research papers and
prototyping models to building data and evaluation tools, debugging
infrastructure, and supporting deployment.
Design training and evaluation workflows, including metrics for safety,
progress, comfort, interaction quality, and robustness.
Analyze model behavior and failure modes, run experiments, and use the results to improve models and data.
Collaborate with control, simulation, data, and other algorithm
teams to integrate and validate new capabilities.

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:
Develop and optimize computer vision and deep learning algorithms to accelerate data generation and labeling workflows for autonomous driving
Apply both classical computer vision techniques and modern deep learning methods to solve large-scale data challenges
Collaborate closely with development and annotation teams to enhance automation and ensure high-quality data
Own the entire lifecycle from prototyping to scalable deployment within internal pipelines and tools
Develop tools to evaluate and analyze algorithm performance, robustness, and operational efficiency.

Required Algorithm Team Lead - Geometric Data Infrastructure
About the team:
The AV Sensing group is responsible for the critical and challenging task of object detection and scene comprehension using LiDAR and Radar sensors. Our team develops scalable infrastructure and algorithmic solutions for processing, validating, and understanding complex 3D sensor data.
What will your job look like:
Lead and mentor a team of ~5 Algo and Software Developers while remaining hands-on and closely involved in technical and algorithmic challenges.
Design and build scalable Python libraries, data workflows, validation and monitoring systems for spatial data.
Develop algorithms and geometric tools for 3D data processing, sensor calibration, coordinate transformations, and spatial relationships.
Build and maintain development infrastructure, including databases, dashboards, CI/CD pipelines, and automated documentation.
Take ownership of complex algorithmic challenges from research through production, while collaborating with cross-functional teams to integrate solutions into the broader system.

Required Algorithm Researcher - Autonomous Driving (CTO Group)
About the team:
The CTO Group is a small, elite team focused on the decision-making module of our autonomous driving system.
Our mission is to solve some of the hardest problems in autonomous driving by combining the full spectrum of modern computer science - from rigorous mathematical modeling, optimization, and algorithm design to deep learning.
The team develops the driving policies that translate system-wide inputs into safe, efficient, and human-like driving behavior. Our work spans classical algorithms, optimization under constraints, probabilistic reasoning, reinforcement & supervised learning, all grounded in real-world driving data.
The group is comprised of top researchers and developers and is led by world-class scientists, offering a unique opportunity to work closely with the CTO, shape the future of autonomous driving, and influence the company's technical direction.
What will your job look like:
Research and develop innovative algorithms for autonomous driving planning and decision-making.
Model complex real-world driving scenarios and formulate them as optimization, learning, or algorithmic problems.
Apply a broad range of techniques - from mathematical modeling and classical algorithms to machine learning and deep learning - to improve driving policies.
Analyze large-scale driving data to gain insights, validate hypotheses, and improve system robustness and performance.
Design and implement high-quality production-ready code in a research-driven environment.
Read, evaluate, and build upon state-of-the-art scientific literature in algorithms, AI, and machine learning.