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We are seeking a Embedded Systems Software Architect to own the technical direction of our embedded software platforms. This role combines hands-on development, system architecture, and technical leadership, guiding a team of embedded engineers while ensuring high-quality, scalable, and reliable software across current and future products.
You will act as the technical authority for embedded software, working closely with hardware, systems, and product stakeholders to translate requirements into robust software solutions.
What will your job look like?
Lead the technical direction and architecture of embedded software platforms across middleware and application layers.
Serve as the technical authority for embedded software, combining hands-on C/C++ development with system-level ownership.
Design scalable, modular software architectures and define clear interfaces between hardware, OS services, middleware, and application software.
Drive key technical decisions, architectural trade-offs, and long-term roadmap.
Develop and integrate middleware and application-layer components, including multi-threaded and real-time logic.
Lead design reviews, mentor embedded software engineers, and promote high coding and architectural standards.
Take ownership of complex system-level debugging, performance optimization, and software quality.
Work closely with OS, systems, product, QA, and manufacturing teams to translate product requirements into robust technical solutions.

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 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 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.

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.

we are looking for an experienced Software and Integration Engineer to join the CTO group and take a key role in delivering robust, large-scale autonomous driving software.
The group is primarily focused on the decision-making module of our company's self-driving car. It leverages a wide range of algorithmic approaches, rigorous formal definitions, and mathematical modeling- enriched by insights drawn from large-scale data and real-world driving experience.
In this role you will play a key role in designing, building, and maintaining Algo utility and software infrastructure within the company's primary algorithmic flow.
What will your job look like:
Take part in technical design and decision-making, balancing performance, scalability, and maintainability.
Debugging real-time oriented code while adhering to high standards of memory management and running-time requirements.
Manage the groups software delivery, ensuring timely, high‑quality releases.
Opportunities to work on cutting-edge projects and technologies in the autonomous driving industry.
Working closely with external algo teams and various departments in our company for requirement gathering and the correct integration of new features.

we are a global leader in autonomous vehicle (AV) technology, pioneering advanced driver-assistance systems (ADAS) and self-driving solutions.
Across the company, Senior Deep Learning Algorithm Developers work at the forefront of AV/ADAS innovation - designing, training, and optimizing deep neural networks for tasks such as perception, mapping, and scene understanding. This includes working with large-scale datasets, leveraging frameworks like PyTorch or TensorFlow, and applying state-of-the-art techniques to tackle complex perception and decision-making challenges in real-world driving scenarios.
At our company, Senior Deep Learning Algorithm Developers contribute across multiple AI domains, with most opportunities in Computer Vision and additional roles in areas such as NLP/LLMs and 3D Perception (Radar, LiDAR, Fusion). This role serves as a central entry point, enabling us to align your expertise and aspirations with the projects and teams where you can make the greatest impact.
What will your job look like?
Design, develop and implement deep learning algorithms to solve complex problems in computer vision
Take ownership of deep learning projects: Compose product requirements, design solutions, oversee execution, and collaborate with talented Algorithm Developers.
Collaborate with cross-functional teams to understand requirements and develop solutions.
Analyze large datasets to improve algorithm performance and robustness.
Research the latest advancements in deep learning, multi-task learning, AI architectures, and apply them to enhance our algorithms.

we are a pioneering force in the autonomous vehicles (AV) industry.
Join us to build the brain behind the car - a large-scale, multi-task neural network that powers the core of our companys autonomous stack.
Youll design and train cutting-edge deep learning models tailored for our custom EyeQ chip, tackling end-to-end challenges and deploying real-world solutions.
From novel architectures and advanced training techniques to performance tuning under tight constraints, youll work closely with software and hardware teams to turn research into high-impact, production-ready systems.
If youre a brilliant, hands-on researcher with a passion for shaping the future - this is your launchpad.
Our team is at the forefront of our companys most advanced AI efforts. As a central hub for deep learning innovation, were trusted with designing the core neural network architecture that powers the companys flagship products. If youre seeking a high-impact role among top-tier researchers and developers - this is the place to be.

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

we are looking for a talented Software Engineer to join a team building an internal, AI-powered platform designed to significantly improve product quality by identifying edge cases and long-tail scenarios in autonomous driving systems.
Using state-of-the-art Vision and Language models, the team is rethinking how training, validation, and stress-testing are done.
This is a highly impactful engineering role focused on building innovative internal products end-to-end- tools developed from scratch that are designed to become part of the companys daily workflows and directly influence core algorithmic and product decisions.
If youre passionate about deep learning-driven products, large-scale experimentation, and owning complex systems from design to production- this is the place for you.
What will your job look like:
Take part in building an AI search platform from scratch, and owning it end to end in a production environment.
Design and implement full-stack solutions, including backend services, frontend interfaces, and database management.
Work with cloud-based systems, containers, and modern software infrastructure to support performance, scale, and reliability.
Collaborate closely with algorithm developers and internal users to expose complex capabilities in a simple, usable way.

We are looking for a Software Engineer to join our Object Detection group and play a key role in managing and enabling data workflows that power our computer vision algorithms.
Our team generates and processes large volumes of diverse data from multiple sources, and we need someone who can bridge the gap between raw data and algorithmic innovation. Working alongside algorithm developers and researchers, you'll be responsible for building robust data pipelines, ensuring data quality, and making complex datasets accessible and actionable for our detection models.
This role requires both strong coding abilities and a deep understanding of data - you'll need to think like an engineer while understanding the unique needs of a research and development-focused algorithmic group. A significant portion of the work is highly independent, meaning you will be expected to drive projects end-to-end, taking full ownership from understanding the initial problem and modeling the solution to executing and delivering it yourself.
What will your job look like:
Design, build, and write the underlying code for large-scale systems handling diverse data from multiple sources
Build and maintain robust data pipelines that enable algorithmic development
Evaluate various optional technologies and take part in decision-making
Own key features and services within the data infrastructure
Ensure data quality and accessibility for detection models and research needs.

we are looking for a Validation & Analysis Project Manager to lead the design and implementation of validation infrastructure for Radar, LiDAR, and sensor fusion systems within the AV Sensing team.
** This role requires working at our Jerusalem offices 1-2 days per week.
What will your job look like:
Own the end-to-end validation process for autonomous sensing systems (Radar, LiDAR, and sensor fusion), from definition to execution
Build the validation infrastructure, methodologies, and workflows required to ensure system robustness and safety
Define validation strategy: test coverage, success metrics, and failsafe verification approaches
Translate product and system requirements into structured validation plans and measurable outcomes
Work in close collaboration with R&D, algorithms, system engineering, and product teams
Identify gaps in testability, observability, and lead solutions to address them
Establish scalable processes for validation, monitoring, and continuous improvement
Present insights, risks, and recommendations to stakeholders to drive decision-making.

we are seeking a Technical Product Manager to join the Core AV Platform group and support the development and delivery of our next-generation AV platforms. This role is execution-oriented and ideal for someone who thrives in complex technical environments and enjoys driving multidisciplinary products from definition through delivery.
What will your job look like?
Own and manage product requirements and execution for a large-scale, multidisciplinary system (HW & SW)
Drive day-to-day execution together with engineering teams, customers, and suppliers
Work closely with cross-functional stakeholders including HW, SW, system engineering, business units, customers and suppliers
Support product planning and feature definition aligned with customer and platform needs
Translate complex technical topics into clear and structured communication
Track progress, manage risks, and ensure timely and high-quality delivery.