Jobs at Mobileye

Lead definition, development, and launch of cloud services for autonomous vehicle applications (routing, ODD, fleet management). Own roadmap, KPIs, metrics, cross-functional alignment, and support sales/onboarding with demos and specs.

Design, build, and deploy AI-driven internal tools and agentic workflows that integrate LLMs to accelerate the SDLC. Architect orchestration layers (tool calling, MCP, memory, RAG), identify engineering bottlenecks, and implement zero-to-one solutions while evaluating models, APIs, and deployment approaches.

Lead execution of autonomous vehicle sensing projects (computer vision, LiDAR, radar, camera) from requirements through implementation. Coordinate R&D, AV, and REM teams, manage customer workshops, test drives, debugging, validation, and ensure delivery to OEM partners.

Design and train large-scale, multi-task deep learning models for Mobileye's autonomous stack. Build end-to-end DL pipelines (data prep, training, evaluation, deployment), optimize models for the EyeQ chip, and collaborate with software and hardware teams to convert research into production-ready systems.

Develop and own application-level real-time embedded software in modern C++ for automotive platforms: design, implement, integrate, test, debug, optimize, and mentor junior engineers while collaborating cross-functionally.

Build and scale ML software and data pipelines to deploy deep learning perception models to edge devices. Integrate neural networks into C++ production systems, optimize runtime performance, design dataset selection and validation, and improve CI/CD and deployment workflows in collaboration with algorithm teams.

Develop and productionize deep‑learning perception models for LiDAR and Radar: build ML data pipelines, integrate neural networks into C++ runtime, optimize latency/memory/throughput for edge devices, design data selection and validation, and improve CI/CD and testing with algorithm teams.

Develop and configure AUTOSAR modules and software components below and on top of the RTE; write design docs, requirements, unit tests; perform integration, debugging (bench and in-vehicle), root-cause analysis, and participate in reviews and customer/OEM meetings.

Lead end-to-end recruitment for a growing R&D unit: design sourcing and hiring strategies, partner with hiring managers, source candidates, manage candidate experience, analyze recruitment data, drive cross-organizational initiatives (diversity, employer brand, EVP), and organize recruiting events and programs.

Design and implement RTOS-based embedded firmware in C, define HW–SW interfaces, develop device drivers, collaborate with system/algo/silicon/hardware teams, and support system integration for automotive radar sensors.

Lead technical discussions and manage execution of platform software commitments to automotive partners. Define product roadmap and release plans, track delivery, remove blockers, and coordinate R&D, systems teams, suppliers, and customers to ensure timely, high-quality embedded software delivery for autonomous driving platforms.

Design and train large-scale, multi-task deep neural networks for autonomous driving, optimize models for the EyeQ chip, develop end-to-end DL pipelines, collaborate with software and hardware teams, and deploy production-ready, performance-tuned systems.

Develop and debug low-level C/C++ software and HW drivers for Mobileye SoC under a custom RTOS on MIPS/RISC-V. Create and maintain system verification and integration tests in simulation, perform board bring-up, JTAG-based silicon debugging, and collaborate with ASIC designers to validate hardware features.

Provide executive support to the VP Operations and leadership team: manage calendars, travel, meetings, prepare agendas/presentations, coordinate division-wide activities and events, track action items, improve administrative workflows, and handle confidential information. Role is on-site at the Jerusalem campus five days per week.

Design and implement high-performance C++ software for embedded automotive systems supporting HD map download, caching, storage, distribution, APIs, and map-based algorithms. Optimize for performance and reliability, collaborate with cross-functional teams, lead technical design discussions, and mentor engineers.

Design, implement, and maintain computer vision and 3D reconstruction algorithms in Python. Move algorithms from research to production, collaborate across teams, and develop solutions for multi-sensor perception and real-world autonomous driving challenges.

Design and develop core components and logic for Mobileye's HD map creation pipeline. Collaborate closely with algorithm and engineering teams to build high-performance, massively parallel map-processing systems using Big Data and Spark technologies. Improve system performance, reliability, and scalability for autonomous driving map production.

Design and implement software to optimize deep learning models (quantization, pruning, compression) for efficient inference on low-power automotive hardware. Develop in Python and PyTorch, collaborate with algorithm teams, run literature research and POCs, and support full software lifecycle including testing and CI/CD.

Drive execution for Mobileye's Geometry algorithm teams: remove blockers, align cross-functional teams, turn strategy into deliverable roadmaps, anticipate risks, join technical discussions, and build scalable processes to deliver high-quality autonomous-driving products on schedule.

Lead productization of autonomous-vehicle features: define roadmap, elicit requirements, set data-driven KPIs, manage cross-functional delivery, support business development and OEM integration, and ensure product quality and adoption.