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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 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 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.

we are a global leader in autonomous vehicle (AV) technology, pioneering advanced driver-assistance systems (ADAS) and self-driving solutions.
Across the company, algorithm developers work at the forefront of AV/ADAS innovation - designing and implementing perception, mapping, computer vision, and decision-making algorithms, typically in Python or C++.
At our company, algorithm developers join a variety of teams across a broad range of domains. This role serves as a central entry point, allowing us to match your expertise and aspirations with the team where you can make the greatest impact.
Algorithm developers at our company contribute to diverse areas of innovation, including:
Detection: Developing algorithms to identify and track road users, lanes, and other key elements of the driving environment in real time.
Object Modeling: Developing algorithms to identify, classify, and measure objects (general, unclassified, etc.), enabling precise scene understanding.
Geometry: Developing algorithms to model road geometry, vehicle motion, and calibrations, providing essential spatial data that supports localization, 3D object placement, tracking, and other core perception tasks.
Mapping: Developing algorithms to create high-definition maps from large-scale, crowd-sourced data to enable precise localization and navigation.
3D Perception & Sensor Fusion: Designing algorithms for 3D reconstruction and multi-sensor reasoning to accurately model and understand the driving environment.
What will your job look like?
Your job will include a combination of algorithm development and programming in Python and C++
Work with image-based data, focusing on extracting and representing spatial information accurately and efficiently
Take initiative in identifying and solving complex algorithmic challenges in a fast-paced development environment
Collaborate closely with engineering and research teams in computer vision, data engineering, and related fields to deliver real-world solutions.

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.