Jobs at Mobileye

Drafts, reviews, and negotiates complex global commercial agreements with customers, vendors, partners, and service providers. Provides practical advice on commercial, regulatory, privacy, licensing, distribution, procurement, and intellectual property matters. Develops legal and compliance processes, leads cross-functional projects, and partners with global business stakeholders. Requires approximately eight years of relevant legal experience, strong negotiation skills, business judgment, and fluency in English and Hebrew.

Research and develop image and video generative models for autonomous driving, focusing on temporal consistency, multiview coherence, controllable scene generation, and world models. Own model experimentation, training, evaluation, and workflow integration. Build scalable Python and PyTorch implementations, collaborate with AI and perception teams, and help shape research direction. Work may include diffusion and flow-based models, foundation models, multimodal systems, distributed training, and large-scale proprietary driving datasets.

Develop and optimize computer vision, deep learning, and geometric modeling algorithms for autonomous-driving lane detection and data-generation workflows. Build scalable internal tools and pipelines, collaborate with development and annotation teams, and evaluate algorithm performance, robustness, and efficiency from prototyping through deployment.

Lead Mobileye’s Release Management team and oversee end-to-end ADAS and autonomous vehicle software releases. Responsibilities include defining release processes, coordinating cross-functional planning, managing governance and readiness reviews, tracking risks and KPIs, resolving blockers, improving automation and delivery pipelines, and developing release management professionals.

Lead product strategy and roadmap for cloud and multi-petabyte data services and AI-native agent products. Own requirements, stakeholder engagement with internal teams and OEMs, cross-functional execution, hands-on validation, release planning, adoption tracking, and product documentation to drive scalable, self-service tooling for engineers.

Build and optimize distributed data, evaluation, and ML pipelines for 3D perception models in autonomous driving. Develop tools for image, video, geometric, and model-output processing; improve memory efficiency, throughput, and computation costs. Own model packaging, distribution, and deployment interfaces, while coordinating data contracts and workflows across research, infrastructure, data, and internal customer teams.

Develop and optimize transformer-based temporal vision models for 3D perception in autonomous vehicles. Analyze errors, improve driving-scene understanding, research advances in 3D detection and perception, and work with large-scale driving datasets. The role requires Python development, rigorous experimentation, mathematical and analytical expertise, and collaboration within a large research-oriented team.

Defines system-level hardware architectures for EyeQ-based automotive compute platforms. Integrates SoCs with MCUs, memories, cameras, radars, lidars, SerDes, and networking components while driving trade-offs involving performance, power, thermal constraints, cost, safety, security, and scalability. Translates customer and product needs into requirements and interface specifications, influences SoC and platform architecture, and collaborates with engineering, product, OEM, supplier, and technology partner teams through design, bring-up, and validation.

Defines system-level hardware architectures for EyeQ-based automotive compute platforms supporting ADAS, autonomous driving, and robotaxi applications. Integrates SoCs with MCUs, memories, sensors, connectivity devices, and other components while driving trade-offs across performance, power, thermal constraints, safety, security, cost, and scalability. Translates customer and product needs into system requirements and interface specifications, collaborates across engineering teams, and supports architecture reviews, customer integration, bring-up, and validation.

Leads end-to-end recruiting for a high-tech R&D business unit, developing sourcing and hiring strategies, partnering with hiring managers, building talent pipelines, supporting candidates, analyzing recruiting data, and leading initiatives around candidate experience, diversity, employer brand, and events. This is a fixed-term position of approximately 10 months and may be filled through a contractor.

Manage execution of autonomous vehicle sensing projects from requirements through implementation for automotive partners and internal AV development. Coordinate R&D, AV, and REM teams, track progress, secure technical approvals, align cross-functional interfaces, and lead customer workshops, test drives, functional tuning, debugging, and validation across sensing features.

Lead end-to-end recruiting for a high-tech R&D business unit, developing sourcing and hiring strategies, partnering with hiring managers, building talent pipelines, supporting candidates, analyzing recruiting data, and leading initiatives involving candidate experience, diversity, employer brand, events, and special projects.

Develop high-precision computer vision and deep learning algorithms for autonomous vehicle localization using surround cameras and HD maps. Design models with Transformers, GNNs, and CNNs; solve 3D geometry, scene understanding, object matching, and spatial reasoning problems; combine learned methods with optimization; analyze driving data; and take solutions from prototyping through production deployment.

Designs high-speed radar hardware boards from architecture through production, including schematics, layout, modeling, simulations, and design reviews. Works with SERDES, LPDDR memory, power circuits, and digital interfaces while collaborating with RF, mechanical, and systems teams. The role requires strong signal and power integrity expertise, board design tool proficiency, and experience developing automotive electronic products.

Leads execution of autonomous vehicle sensing products from requirements through implementation. Manages complex R&D projects, tracks development progress, aligns technical requirements, coordinates cross-functional teams, and ensures coherent product delivery. Works with automotive partners through workshops, test drives, and functional tuning, while overseeing debugging and validation across the autonomous sensing stack.

Lead the Board Design and Layout team developing compute hardware platforms for autonomous driving. Manage end-to-end hardware projects from architecture and board design through validation and mass production. Provide technical direction, resolve complex hardware and system-level challenges, collaborate cross-functionally, and maintain customer relationships while ensuring quality, performance, reliability, and manufacturability at scale.

Research and develop reinforcement-learning driving planners for complex interactive road scenarios. Design policy architectures, rewards, training objectives, and optimization methods; evaluate safety, comfort, progress, and interaction quality; analyze closed-loop failures; build simulation-based workflows; and transition research into reliable autonomous-driving components validated on real vehicles.

Leads complex, long-cycle sales engagements with automotive OEMs and Tier 1 suppliers in the ADAS ecosystem. Owns strategic account commercial strategy from RFQ/RFI through negotiation and execution, builds executive relationships, manages pricing and commercial terms, and translates technical capabilities into business value. Coordinates with business development, product, finance, legal, and executive teams while advancing complex hardware and software deals.

Lead technical data product solutions for autonomous-driving algorithm development. Translate research and engineering needs into technical requirements, define data tools and infrastructure, improve data structures and workflows, resolve lifecycle bottlenecks, build prototypes and internal tools, and optimize data quality, availability, storage, usage, and costs with cross-functional teams.

Research and develop reinforcement-learning driving planners for complex interactive road scenarios. Responsibilities include policy architecture, reward design, training optimization, evaluation metrics, simulation-based training, closed-loop failure analysis, and validating improvements on real vehicles. The researcher will translate ideas into reliable autonomous-driving components while collaborating with control and algorithm teams.