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We are looking for a skilled and motivated Embedded SW Integration Team Lead for the Platform OS Department to manage the daily integration of the OS deliveries into our SW stack. The Platform OS team is leading a global effort of making the Linux OS as the Automotive Safety OS that will fuel the Autonomous Vehicle and the whole automotive industry. Youll lead a fast-paced, hands-on and dynamic team of integration and automation engineers, contributing to the overall qualification and integration effort while collaborating with other teams across the organization.
What will your job look like:
Lead and mentor a team of 4-6 SW Integration and Automation engineers
Manage the daily integration of the aggregated delivery of all OS teams upstream into our SW stack.
Daily tracking of changes coming from OS development teams and controlling their integration order, priorities, test coverage and conflicts.
Managing a daily integration forum to track nightly tests reports, triaging new issues found and assigning them to development teams.
System level understanding of the OS features and tracking the test coverage developed by the OS developers.
Tracking the utilization, health and allocation of the HW resources in the farm.
Balancing test coverage to HW availability through tracking CI load.
Acting as a PoC for all OS integration issues. Both within the OS teams and externally.
Tracking bug escapes and their mitigation in the OS test coverage.

We are looking for an Embedded Software Engineer for performance verification and profiling.
You will join the Virtual Platforms and Performance Verification team in the EyeQ Platform Group (EPG), working on current and next-generation ADAS/AV systems.
Virtual platforms, performance models, and profiling tools are core components of the EPG infrastructure. These tools are used during the pre-silicon phase for hardware architecture optimization and software development, and in the post-silicon phase for software performance optimization.
What will your job look like:
Performance verification of EyeQ SoC designs
Development of hardware virtual platforms
Running hardware benchmarks and correlating virtual platform results with silicon measurements
Development of tracing and profiling tools for CPU performance analysis and optimization
Close collaboration with hardware architects and software, OS, and algorithm teams.

We are looking for a Linux kernel expert with deep knowledge in the PCIe standard. As a Linux Kernel PCIe Architect, you will be part of the OS Architecture team and will be responsible to define the operating system solutions based on the PCIe standard for connectivity with peripherals and as an interconnect between multiple EyeQ SoCs.
This is an exciting and unique opportunity to work with highly talented Linux OS architecture and developments teams and be a leader in the definition of the cutting-edge technology for the Automotive AI applications.
What will your job look like?
Researching and defining the SW solutions based on the PCIe standard and the Linux implementation for the PCIe stack
Designing and Implementing the SW Stack for the communication between the EyeQ SoCs laying the infrastructure for cross chip neural networks.
Defining the future HW solutions by working closely with the SoC Architecture team in a SW/HW co-development environment.
Performing performance analysis, feasibility studies, PoCs and optimization flows to achieve the highest performance with minimal resources.
Work closely with the Linux Kernel team and provide the technical guidance and mentoring for development engineers.

We are looking for a Deep Learning Tech Lead for Objects Modeling, who will be challenged by solving real-world problems using Computer Vision. Our mission in the algorithms department has a significant impact on autonomous vehicle technologies, external customers, and advanced driver-assistance systems (ADAS). In this role, you will be responsible for the full cycle of deep learning R&D, including modeling new solutions and enhancing the performance of existing ones. Your responsibility will include design, implementation, guidance and mentoring for team members. You will leverage your extensive experience to lead multiple deep projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
This role offers the flexibility to work part-time from our other sites, subject to seat availability.
What will your job look like:
Lead the design, development, and implementation of accurate and robust AI algorithms for new projects
Research the latest advancements in deep learning, multi-task learning, AI architectures, and apply them to enhance our algorithm
Design, develop and implement deep learning algorithms to solve complex problems in computer vision
Take ownership of deep learning projects: Design solutions, oversee execution, and collaborate with talented Algorithm developers
Collaborate with cross-functional teams to understand requirements and develop solutions.

Required Deep Learning Algorithm Engineer - REM Semantics
You will be part of our REM (Road Experience Management) department which is responsible for the automatic High Definition map-making process, which is a key technology in our autonomous driving and high-end Driving Assistance systems.
You will be joining the team that builds the state-of-the-art AI-powered relevancy systems at scale. You will be designing and implementing semantic understanding engines that power data-driven products across autonomous driving and beyond, combining cutting-edge Computer Vision, Graph Neural Networks, and efficient inference to solve real-world perception challenges.
If you're talented, highly motivated and passionate about building intelligent systems where your contributions drive concrete, measurable outcomes, we'd love to meet you.
What will your job look like:
Conduct hands-on research and development of AI and Deep Learning algorithms for real-world automotive perception tasks
Own projects end-to-end - from concept, through research, prototyping, designing, training, and evaluating neural network architectures, to integration and scalable deployment
Analyze challenging edge cases and continuously improve model performance in complex driving scenarios
Collaborate with algorithm developers, software engineers, product managers and system teams across the organization
Work with large-scale datasets and real-world driving scenarios to improve model accuracy, robustness, and runtime efficiency
Bring your ideas into production-ready systems that have a direct, measurable impact on autonomous vehicle technologies used worldwide

Required Backend Team Lead - REM Engineering
As the Backend Team Lead for REM Ingestion, you will spearhead the design, development, and scaling of the critical entry point for our Road Experience Management (REM) platform. Your team is responsible for capturing, processing, and validating massive streams of crowdsourced data from millions of vehicles worldwide in real time.This is a hybrid leadership and technical role. You will lead a squad of engineers while remaining hands-on in architecting resilient, ultra-high-throughput distributed systems that power the future of autonomous driving and advanced mapping.
What will your job look like:
Drive Execution: Balance hands-on development (coding, code reviews, and architecture) with project management, resource planning and delivery.
Architect at Scale: End-to-end architecture of ingestion pipelines capable of handling massive scale, ensuring low latency, high availability, and optimal cost-efficiency.
Lead & Mentor: Empower, guide, and scale a talented team of backend engineers. Foster a culture of technical excellence and continuous learning.
Optimize Infrastructure: Continuously improve system performance, data throughput, and cloud infrastructure utilization (compute, storage, and networking costs).

Required Algorithm Team Lead
Join our innovative team, where you will lead a talented Deep Learning R&D team developing advanced neural networks that are essential for our key products.
In this role, you will lead a team responsible for developing real-time vision models that power the vehicles understanding of its environment. The team combines research, hands-on development, model training, data analysis, optimization, and product-grade delivery for autonomous driving technologies and advanced driver-assistance systems.
As a Deep Learning R&D Team Lead, you will be responsible for both the technical and managerial leadership of the team. You will guide the full development cycle of deep learning solutions - from understanding the problem and data, through modeling and training, to performance improvement, validation, and delivery into production systems.
What will your job look like?
Lead a small and highly capable Deep Learning R&D team working on real-time computer vision models for our products.
Provide technical leadership across the full deep learning development cycle, including data understanding, model design, training, evaluation, optimization, and production readiness.
Drive goal-oriented research and development, balancing innovation with practical product needs, timelines, and delivery quality.
Mentor, support, and develop team members, while creating a strong professional environment that encourages ownership, creativity, and continuous improvement.
Break down complex and ambiguous problems into clear work plans, priorities, milestones, and execution steps.
Collaborate closely with cross-functional teams to understand requirements, align expectations, and deliver effective solutions.
Improve existing models and development flows to enhance accuracy, robustness, runtime performance, scalability, and product impact.
Stay up to date with the latest advancements in deep learning, computer vision, AI architectures, and AI-based development tools, and apply relevant ideas to improve the teams work.