Camera System Architect 摄像头系统工程师

该职位来源于猎聘

Objective: 人工智能正在深刻变革汽车行业，带来巨大商业机遇。作为豪华车企，梅赛德斯 - 奔驰致力于依托人工智能驱动的产品与服务塑造未来出行，提升安全性、驾乘便利性与可持续性。为扩充现有团队，我们正在招聘一名摄像头域高级系统架构师。该岗位全权负责摄像头端到端系统架构设计与全栈交付，涵盖摄像头硬件、驱动、图像信号处理器（ISP）、图像调优、摄像头服务及应用层。 Main Tasks: 1.在多款片上系统平台上设计并落地可量产的复杂车载摄像头系统方案，负责整体系统架构设计、技术验证、性能优化，保障系统稳定性、可扩展性，满足汽车量产及功能安全相关标准。 2.全权负责摄像头全栈系统开发与迭代，包含硬件规格定义、底层驱动调试、图像信号处理器链路配置与调优、安卓车载系统摄像头服务优化，以及端到端应用层集成工作。 3.牵头多摄像头并发码流系统的架构设计与性能优化，攻克系统资源调度、带宽瓶颈、延迟抖动、画面帧稳定性等核心难题，保障复杂车载摄像头系统可靠运行。 4.推动摄像头系统与车载人工智能平台深度集成，设计基于摄像头的多模态感知功能技术方案，支撑智能车辆多模态功能的开发、调试与量产交付；与外部供应商及合作伙伴紧密协作，保障感知人工智能模型稳定部署。 5.在整车大型项目中组织供应商与子系统架构师开展跨域架构评审，对齐各模块技术规范，解决架构冲突与系统级技术风险，统一摄像头系统整体设计标准。 Qualification: 1.计算机、电子工程或相关专业本科及以上学历，5 年以上智能车载摄像头系统架构、全栈开发相关工作经验。 熟练使用 C/C++ 嵌入式编程，掌握嵌入式系统原理；具备完整的摄像头端到端全栈技术能力，覆盖摄像头硬件、驱动、图像信号处理器调优、硬件抽象层、安卓车载摄像头框架、数据流处理以及上层应用适配。 2.扎实的计算机视觉基础，理解视觉感知原理与人工智能模型部署机制；能够通过摄像头与人工智能系统高效集成、自适应调优，落地车载多模态功能。 3.具备多摄像头码流系统性能调优、多片上系统平台下复杂摄像头方案设计的实战经验；能够对接多家供应商并完成项目交付。 优秀的系统架构思维与跨领域协作能力，有大型整车跨子系统项目、供应商架构评审实操经验；能够独立攻克系统层面技术瓶颈，推动技术突破。 4.优秀多任务处理能力，具备战略思维、分析能力与问题解决能力。 良好沟通与人际交往能力，具备英语读写及口语沟通能力。 Objectives Artificial Intelligence is changing the automotive industry extensively and brings with it huge business opportunities. As a premium manufacturer, Mercedes Benz is committed to shaping the future of mobility through AI-driven products and services that enhance safety, convenience, and sustainability. To strengthen our current team, we are looking for a senior system architect focusing on the camera domain. The role owns end-to-end camera system architecture design and full-stack delivery covering camera hardware, driver, ISP, image tuning, camera services and application layers. Main tasks -Design and deliver complex, production-grade automotive camera system solutions across multiple SoC platforms, responsible for overall system architecture design, technical verification, performance optimization, and ensuring system stability, scalability and compliance with automotive mass-production and functional safety standards. -Own full-stack camera system development and iteration, covering hardware specification, low-level driver bring-up, ISP pipeline configuration & tuning, Android Automotive camera service optimization, and end-to-end application-layer integration. -Lead the design and performance optimization of multi-camera concurrent streaming systems, resolve core challenges including system resource scheduling, bandwidth bottlenecks, latency jitter and frame stability to support reliable operation of complex in-vehicle camera systems. -Drive deep integration between camera systems and in-car AI platforms, design technical solutions for camera-based multimodal perception features, and support the development, debugging and mass delivery of intelligent vehicle multimodal functions; collaborate closely with external suppliers and partners to ensure robust perception AI deployment. -Host cross-domain architecture reviews with vendors and subsystem architects in large-scale vehicle projects, align cross-module technical specifications, resolve architecture conflicts and system-level technical risks, and unify overall camera system design standards. Qualifications -Bachelor’s degree or above in Computer Science, Electronic Engineering or related fields, with 5+ years of professional experience in automotive intelligent vehicle camera system architecture and full-stack development. -Proficient in C/C++ embedded programming and embedded system principles; possess comprehensive end-to-end camera full-stack expertise covering camera hardware, driver, ISP tuning, HAL, Android Automotive camera framework, data flow processing and upper-layer application adaptation. -Solid computer vision knowhow, with a clear understanding of visual perception principles and AI model deployment mechanisms; capable of enabling vehicle multimodal features via efficient camera-AI system integration and adaptive optimization. -Proven experience in multi-camera stream system performance tuning and complex camera solution design across diversified SoC platforms; capable of cross-vendor technical docking and project delivery. -Strong systematic architecture thinking and cross-domain collaboration capabilities, with hands-on experience in large-scale automotive cross-subsystem projects and vendor architecture reviews; able to independently tackle system-level technical bottlenecks and drive technical breakthroughs. -Strong multi-tasking capabilities;Strategic thinking, analytical, and problem-solving skills -Excellent communication and interpersonal skills. -English in written and spoken