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We are looking for an Algorithm Developer who will be challenged to solve real-world problems using Computer Vision and Signal Processing techniques. Our mission in the Algorithms department has a significant impact on autonomous driving technologies and on saving lives.
In this position, you will combine classic programming and algorithm development in Python and C++, and be responsible for maintaining the product and developing new features. As an Algorithm Developer, you will learn and develop new algorithms that can address new problems and challenges as they arise.
The work in our algorithms department is dynamic and involves developing algorithms from the early stages of research through to production, while collaborating with other teams throughout the organization.
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.
You will need to learn and develop new algorithms that can address new problems as they arise.

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're looking for a talented Robotics Algorithm engineer to join our team and develop cutting-edge perception and localization capabilities for autonomous systems. Design, develop, and optimize algorithms for SLAM, Mapping, Localization, Sensor Fusion, and State Estimation. Build robust solutions using data from LiDAR, Cameras, IMU, GNSS, and Odometry sensors. Implement and improve graph-based optimization and probabilistic estimation algorithms. Integrate Machine Learning and computer vision techniques into perception and navigation pipelines. Develop, TEST, and validate algorithms in simulation and real-world environments. Optimize software for Real-Time performance on Embedded and edge computing platforms.

In this role, you will be leading all aspects of verification and will have a critical impact on the company's R&D path.



Responsibilities:

Define and implement robust SV/UVM verification solutions, including test benches and methodologies, to drive efficient verification closure across block-level and full-chip designs, integrating Mix-signals SoC simulation environment using Verilog, MATLAB, HW/SW Co-simulation and lab integration.
Work closely with Digital Design, Analog Design, Software, Back-end, SW and System teams to understand the functional, power and performance goals of the product and ensure its quality.

In this role, you will be leading all aspects of verification and will have a critical impact on the company's R&D path.



Responsibilities:

Lead the full verification lifecycle and methodologies. Plan, Design and Execute verification of SV/UVM Block level and Full chip environments , creating and execution test plans, tracking progress, and ensuring verification closure across diverse Mix-signals SoC simulation using Verilog, MATLAB, HW/SW Co-simulation and lab integration.
Work closely with Digital Design, Analog Design, Software, Back-end, SW and System teams to understand the functional, power and performance goals of the product and ensure its quality.

We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will work at the intersection of machine learning, quantum physics, and software engineering, translating noisy, non-stationary, safety-critical control problems into ML solutions that run on real hardware in production labs.

You will develop reinforcement learning policies, Bayesian inference methods, and agentic frameworks that make quantum control more autonomous, more sample-efficient, and more robust to drift. This position offers unprecedented exposure to diverse qubit types and quantum architectures, with a tight feedback loop between your models and the systems they steer, and the opportunity to deliver groundbreaking ML-driven solutions to the labs and companies defining the next generation of quantum systems.

Responsibilities:

Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
Develop real-time parameter steering for calibration during QEC and between circuits.
Develop and maintain agentic frameworks for autonomous system control and calibration.
Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.

We are looking for a highly experienced a hands-on Compiler Engineer who embodies ambition and positivity.

Someone who can passionately take ownership of their responsibilities, collaborating effectively with remote teams to not only meet but exceed our objectives and fulfill the evolving needs of our expanding customer base.

Requirements
Responsibilities:

Develop compiler from a proprietary quantum language to a proprietary processor tailored to realize and accelerate quantum computing.
Take on complex optimization challenges at the core of our unique compiler, focusing on real-time applications, hybrid quantum/classical algorithms, and parallel processing.
Conduct rigorous testing, debugging, and profiling to ensure the performance and correctness of compiler outputs.
Hands-on development and debugging of software to optimize the utilization of limited hardware resources, enabling the scaling of quantum computing systems and improving quantum algorithm performance on our cutting-edge quantum orchestration platform.
Collaborate closely with hardware, software and architecture teams to ensure seamless software-hardware integration, directly enhancing system capabilities and performance.

We are looking for a Verification Engineer who embodies ambition and positivity, who can passionately take ownership of their responsibilities, collaborating effectively with remote teams to not only meet but exceed our objectives and fulfil the evolving needs of our expanding customer base.

The Verification engineer we look for will be a highly talented and motivated person, who is a real team player and can collaborate closely with engineers from other disciplines and quantum physicists.

Responsibilities:

Practicing the full range of verification aspects
Creating a verification environment from scratch (drivers, monitors, coverage...)
VIP (DDR/PCIe/AXI) integration
Defining verification sequences via a complex control-flow constraint set
System understanding of a full-stack product with strong HW-SW coupling
Reference model integration
Test plan definition
Defining verification flows and creating the proper infrastructure to support it

We are looking for a Verification Engineer who embodies ambition and positivity, who can passionately take ownership of their responsibilities, collaborating effectively with remote teams to not only meet but exceed our objectives and fulfil the evolving needs of our expanding customer base.

The Verification engineer we look for will be a highly talented and motivated person, who is a real team player and can collaborate closely with engineers from other disciplines and quantum physicists.

Responsibilities:

Practicing the full range of verification aspects
Creating a verification environment from scratch (drivers, monitors, coverage...)
VIP (DDR/PCIe/AXI) integration
Defining verification sequences via a complex control-flow constraint set
System understanding of a full-stack product with strong HW-SW coupling
Reference model integration
Test plan definition
Defining verification flows and creating the proper infrastructure to support it

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.