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As a Silicon Engineering Manager you will be responsible for improving silicon-photonics yield and performance through data-driven analysis, cross-functional collaboration and proactive issue resolution.

You will serve as the key interface between R&D, Process and Production teams, ensuring efficient data flow, rapid issue identification and continuous process improvement across wafer fabrication, device testing, and packaging stages.

Responsibilities
Perform silicon process and chip-level data analysis, establishing correlation between chip and wafer performance.
Lead process debug and yield loss analysis at chip/wafer level, driving root cause investigations and corrective actions.
Manage engineering approval forum to release production material.
Collaborate closely with vendors to implement new product tests and resolve technical/process issues.
Act as a key interface between design, testing, and production teams, ensuring alignment across the product lifecycle
Oversee and coordinate the transfer of data related to silicon design, testing, fabrication, and characterization between Production and R&D departments.
Develop and implement data management strategies to ensure data accuracy, security, and accessibility.
Maintain proper documentation of data transfer protocols, version control, and data integrity checks.
Support data analysis efforts to improve silicon performance, yield, and quality.
Ensure compliance with company policies and industry standards related to data security and confidentiality.

we are looking for an Emulation Engineer to join our Radar VLSI team and drive the development of next-generation ASIC Sensors.
We are developing best-in-class automotive radar solutions to complement our companys autonomous driving platform. Joining our expert team, you will leverage our companys unique assets to work on cutting-edge technology in a dynamic and challenging environment.
What will your job look like?
In this role, you will build high-end Emulation environments based on new designs. The position involves building and integrating complex components, working with cross-functional engineering teams, and developing systems that will change the way we drive.
We are looking for an engineer who thrives on challenges and is committed to engineering excellence while navigating complex constraints.
Lead Emulation development for the VLSI team.
Work closely with SW, Logic, and Verification engineers.
Serve as an expert matter for your domain, with full responsibility for driving and implementing improvements and new ideas.

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, 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, 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).
Signoff : on all physical design domains- STA, IR/EM, Physical Verification, Logic Equivalent Checking, Low Power Verification.

We are looking for a Photonics Layout Engineer to join our integrated photonics design team.

This position is also well-suited for Analog Layout Engineers who are interested in transitioning into photonic integrated circuit (PIC) design.

In this role, you will be responsible for creating, optimizing and validating PIC layouts, ensuring manufacturability, performance and compliance with foundry design rules.

You will work closely with device designers, process engineers and tape-out teams to deliver high-quality layouts of silicon photonics PICs.

Strong candidates will have hands-on experience with industry-standard layout tools, especially Cadence Virtuoso or similar software.

Understanding of photonic components, waveguide routing and automated layout generation is a major advantage.

You will also contribute to layout methodologies, PCells, and design automation flows to accelerate PIC development.

Responsibilities

Develop and implement mask layouts for photonic integrated circuits using Cadence Virtuoso or similar software.

Create and maintain PCells for photonic building blocks (waveguides, couplers, modulators, gratings, etc.).

Perform waveguide routing, ensuring correct connectivity, bend radius limits, and low-loss optical paths.

Verify layouts using DRC, and LVS to ensure compliance with foundry requirements.

Collaborate with device designers to translate basic schematics and specifications into Software schematics and manufacturable layouts.

Optimize layouts for performance, yield, and compactness while adhering to technology constraints.

Participate in photonic design automation tool development and workflow improvements.

Prepare and manage data for tape-out and support mask review processes.

Debug layout and rule-check issues and propose corrective actions.

our company SOC verification group owns the important and challenging job of verifying our company's 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.

our company SOC verification group owns the important and challenging job of verifying our company's 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.

We are seeking a hands-on Program Manager (PMO) to lead complex customer programs in a fast-growing, multidisciplinary deep-tech environment.

This role drives execution across customers, R&D and operations teams, owning programs from early design engagement through data centres qualification and production ramp - directly enabling customer adoption, predictable delivery, and revenue growth.

Responsibilities
Own end-to-end execution of customer programs - from design-in through DC qualification and production ramp.
Drive on-time delivery of milestones and customer commitments in complex technical environments.
Act as the execution focal point between customers, R&D and operations teams.
Build and scale multi-customer execution frameworks that support company growth.
Proactively identify risks, remove blockers, and minimize escalations across programs.
Ensure high-quality delivery while protecting engineering focus.

our company's ML Platform group builds and operates the core infrastructure that powers large-scale AI workloads across on-prem bare-metal GPU clusters and multi-cloud environments. Our goal is to deliver the modern infrastructure and tooling that accelerates our company's entire algorithm development lifecycle - from a researcher's first experiment to a production deployment.
We are a small, independent group of engineers with diverse skills across software, infrastructure, and systems. We set the standards, build the cross-company products, and take end-to-end ownership of everything we ship.
What will your job look like?
Design, develop, and maintain the Python framework that enables algorithm developers across our company to train, validate, quantize, and deploy deep learning models - locally, on-prem, and across cloud providers - through a single unified interface
Build high-performance data streaming libraries that feed large-scale distributed training pipelines in Rust with Python interfaces
Set the standard for reliable, reproducible research at scale - experiment tracking, configuration management, checkpoint handling, and multi-node training
Work directly alongside algorithm researchers to understand friction, propose solutions, and ship them - without layers of process in between
Contribute to open source when the right fix/feature belongs upstream.

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.