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The SW validation team plays a key role in enabling the next generation of autonomous driving technologies. In their primarily Python-based development environment, they are responsible for developing and maintaining test content for the autonomous vehicle brain, supporting complex end-to-end validation flows across the system.
As part of the full autonomous driving pipeline, they work closely with cutting-edge technologies and gain direct exposure to the real-world impact of their work - helping bring some of our companys most advanced autonomous driving capabilities from development into reality.
What will your job look like:
Be the technical lead of the team that is responsible for the development of test content (mostly in Python) for the autonomous vehicle system and E2E flows
Review and approve system architecture requirements
Design and implement complex test solutions
Enforce compliance with autonomous vehicle industry standards.

The Road Algorithm team is responsible for one of the most critical and challenging tasks in autonomous driving - detecting and understanding the drivable road. Our work leverages Deep Neural Networks and geometric modeling to deliver reliable and high-quality road perception for autonomous vehicles.
We are looking for an Expert Deep Learning Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities.
What will your job look like:
Conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
Lead exploratory investigations into new architectures, training strategies, and data utilization methods
Join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
Own projects end-to-end - from concept and experimentation to integration and scalable deployment.

The Road Algorithm team is responsible for one of the most critical and challenging tasks in autonomous driving - detecting and understanding the drivable road. Our work leverages Deep Neural Networks and geometric modeling to deliver reliable and high-quality road perception for autonomous vehicles.
We are looking for an Expert Deep Learning Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities.
What will your job look like:
Conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
Lead exploratory investigations into new architectures, training strategies, and data utilization methods
Join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
Own projects end-to-end - from concept and experimentation to integration and scalable deployment.

we are at the forefront of revolutionizing the automotive industry with its cutting-edge autonomous vehicle (AV) technology. If you're a highly skilled and driven individual who thrives on innovation and wants to shape the future of transportation, come join us! We are seeking a dynamic and experienced Integration Engineer to be part of our Optimization team.
This role uniquely combines the responsibilities of a Software Integrator and a CI Engineer. As a key player in our growing software group, you will design, support, and build automated code testing environments, ensuring a smooth integration process for our software components. Your expertise will directly contribute to our intensive development process while maintaining robust, live production environments. Join us to make a difference in how the world drives!
What will your job look like:
Manage version releases and ensure timely delivery of AV products to stakeholders.
Collaborate with developers to integrate complex software components into a cohesive whole.
Partner with downstream integrators in the deployment pipeline to ensure seamless delivery.
Leverage and utilize GenAI tools and LLM-driven automation to improve and accelerate the software integration and debugging process.
Analyze source code, resource constraints, and test scenarios to identify, prioritize, and resolve integration and performance issues.
Debug complex, multi-domain issues in production and hardware-validation platforms.
Develop, enhance, and maintain automated scripts and CI pipelines for diverse development and validation teams.
Contribute to the continuous optimization of our AV infrastructure and core software codebase.
Build robust, scalable CI solutions utilizing Python, Shell scripting, Jenkins, and Docker.

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
** The role includes working on-site at our Jerusalem office several days per week.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

Which department will you join?
Our Physical Design group operates in a dynamic, startup-like environment that values deep technical expertise and high-level execution. Each engineer holds end-to-end responsibility - from initial definition and constraints development to execution and full signoff. You will work closely with Design and Architecture teams on RTL modifications and design reviews to ensure seamless convergence.
Were looking for a Physical Design Engineer to join our growing team, and take a key role in developing our next-generation SoC from definition to Tape-Out.
What will your job look like:
Hands-on physical design block owner, leading the process from RTL to GDS .
Lead floorplan exploration in collaboration with Front-End and Architecture teams.
STA: Partner with FE and floor planners to manage block and top-level constraints and perform 1st-level timing analysis.
Synthesis: Conduct synthesis exploration and deliver final netlists, including scan insertion, UPF, and clean Lint/Spyglass checks.
Place & Route: Drive the flow from synthesis netlist to final layout and signoff verification, with a focus on optimizing PPA (Power, Performance, and Area).

Our Physical Design group operates in a dynamic, startup-like environment that values deep technical expertise and high-level execution. Each engineer holds end-to-end responsibility - from initial definition and constraints development to execution and full signoff. You will work closely with Design and Architecture teams on RTL modifications and design reviews to ensure seamless convergence.
Were looking for an Experienced Physical Design Engineer to join our growing team, and take a key role in developing our next-generation SoC from definition to Tape-Out.
What will your job look like:
Hands-on physical design block owner from RTL to GDS with horizontal ownership.
Floorplan exploration and collaboration with front-end and architecture teams.
Synthesis exploration and final synthesis including: SDC definition, Scan insertion, Lint, LEC, UPF-LP & Spyglass verification.
Place & Route: from Synthesis to final layout and signoff verification on all tools and floors, with target to achieve best PPA.
STA: timing analysis, working with Sub System and Full Chip owners to manage block and top level constraints for synthesis, P&R and signoff.
Signoff : on all physical design domains- STA, IR/EM, Physical Verification, Logic Equivalent Checking, Low Power Verification.

we are looking for a driven and technically fluent Product Manager to join the MECI Group within the Software Engineering organization. The MECI Group enables our companys algorithmic development flow by building scalable CI, build, test, and AI-driven tooling that supports the full development lifecycle. Our platforms allow our company to scale efficiently and increase development velocity, while maintaining high standards of reliability, collaboration, and developer well-being. As a Product Manager in MECI, you will own and evolve core internal platforms that are foundational to how our company develops, validates, and delivers algorithms. This role sits at the intersection of engineering, infrastructure, and developer experience, with broad impact across Algo, Validation, and Platform teams.
Why this role is unique
This role offers end-to-end ownership of products that are central to our companys development ecosystem. You will lead products spanning development workflows, build and test systems, platform services, and AI-assisted tooling, operating across multiple teams and technical domains. The role combines strategic product leadership with hands-on collaboration in a highly technical environment, where scale, performance, and reliability are critical. Youll work closely with engineering leaders and cross-functional stakeholders to identify high-impact problems, define clear priorities, and drive delivery of solutions that measurably improve productivity, platform stability, and developer experience.
What your job will look like:
Own the product vision, strategy, and roadmap for key MECI platforms and capabilities
Drive cross-organizational alignment on platform priorities, architectural evolution, and adoption strategy
Translate needs from Algo developers, Validation teams, CI users, and Infrastructure stakeholders into clear product requirements, specifications, and user flows
Lead the full product lifecycle - from discovery and problem definition, through design and implementation, to rollout, monitoring, and continuous improvement
Maintain ongoing engagement with users to deeply understand workflows, pain points, operational constraints, and opportunities for improvement
Partner closely with engineering leadership on prioritization, scope, and delivery, balancing short-term needs with long-term platform health
Contribute to building a culture of collaboration, ownership, and sustainable development, with attention to developer well-being.

High-quality labeled data for REM production programs and our mapping products and tools. We run an operation that deploys labeling for production-scale projects, applies high-standard quality assurance, and then manages and consumes large volumes of data end to end - from annotation through delivery into mapping pipelines.
What will your job look like:
Support ongoing annotation work for REM production programs and mapping deliverables, keeping day-to-day labeling aligned with specs and priorities.
Analyze issues and drive fixes in labels, guidelines, tooling gaps, and vendor output so root causes are addressed
Own and improve quality and efficiency of annotation workflows (QA, rework, throughput) without trading accuracy for speed.
Collaborate across teams - product, mapping, algorithms, operations, and vendors-to align requirements, timelines, and acceptance criteria.
Understand REM technology and real-world map behavior so annotations reflect how roads, lanes, and scene context behave in actual driving.
Work with map and imagery data from many regions (countries, cities, and driving cultures) and keep labeling consistent across geographies.
Run continuous project reviews and produce clear, regular reports on status, risks, quality, and delivery.
Meet project KPIs for label quality, coverage, and schedule
Train and coach offshore annotation engineers on REM concepts, tools, edge cases, and quality expectations.
Interpret complex driving scenes via maps and related data and turn that understanding into practical guidance, specs updates, and scalable solutions for the labeling team.

we are looking for a Real-Time Embedded DSP Software Engineer to join the development of state-of-the-art automotive imaging radar technology.
Our vision is to bring new and cutting-edge automotive radar sensor solutions, while leveraging our companys assets and expertise in this field. Introducing best in class Radar sensor that would complement our companys end-to-end autonomous driving solution platform
You will be part of a winning team in a fast-paced startup-like environment, working on many different components of the entire system. You will have an opportunity to make an impact on the design and implementation of an innovative technology in its early stages.
What will your job look like?
Design, build and optimize software modules for production grade imaging-radar solution
Implement complex algorithms in a multi-core platform with high bandwidth with distributed memory
Work closely with algorithms teams to convert complex MATLAB code to efficient real-time environment.
Plan memory arrangement, data transfers and pipelining of computation, to maximize DSP utilization.

We are looking for Junior Physicist to be part of the laser and silicon photonics testing and characterization group.

Responsibilities:
Develop new testing methods, plan experiments and analyze test results to enable new product development.
Characterize the performance of lasers and various photonic devices over different conditions to ensure they meet target specs.
Participate and assist in Failure analysis and yield improvement investigations.

we are looking for a Safety Architect to join the Safety team. This team develops novel approaches to assess and promote autonomous vehicle (AV) safety.
Safety is a core decision driver at the highest level of our company development and business strategy, directly impacting project timelines and approval for our most advanced programs.
Demonstrating that an autonomous vehicle is safe is a cutting-edge challenge. It requires a deep understanding of the entire AV system, the development of robust methods and tools to support this goal, and active engagement with the automotive industry to build broad acceptance of our approach.
What will your job look like?
Analyze the SW architecture and identify safety-critical areas, define the safety requirements and work closely with R&D teams to reach the best solutions
Support the SW system architecture definition of the company automated driving system
Define the safety requirements for high-level components of the company autonomous vehicle products including driving applications, image processing, memory management, error handling
Act as a POC for R&D teams in terms of Safety and embed the Safety culture, train and guide safety ambassadors within the teams
Proactively support our company position with customers during business development activities and during the execution of production projects.

We are looking for Junior Device and Test Engineer.

Responsibilities:
Implement electro-optical test plans for products under development or qualification.
Support testing and characterization stations in the RND labs.
Develop and improve methods for testing and characterization of Silicon photonics devices.
Analyze Test data and DOE results to provide vital insight into the development of innovative silicon photonics products.
Support cross-functional failure investigations to identify root cause and corrective and preventative action.

What will your job look like:
Design and optimize algorithms and pipelines for large scale model inference
Build scalable systems for high throughput data processing and streaming
Develop data transformation and preprocessing components for ML workloads
Improve performance, efficiency, and reliability across distributed inference systems
Work closely with ML researchers, infrastructure, and platform teams
Drive architectural decisions for production ML and data systems.