【智新】深度学习算法工程师 深圳、杭州 社招 全职 互联网 / 电子 / 网游 职位描述 1.负责图像/视频相关算法的研究与开发，将深度学习CV算法与安防应用场景相结合，并突破所有应用瓶颈；2.对大量业务场景数据进行预处理，并能高效运用于模型训练且有效提升模型精度；3.负责跟踪与研究业界最先进的计算机视觉和图像处理算法，并结合公司产品的需求将算法落地实现商用等。 职位要求 1、硕士以上学历，专业要求：图像处理、计算机视觉、人工智能、应用数学、自动化等计算机、机器学习相关专业；2、对深度学习的基本原理有深刻理解，包括但不限于：CNN/ViT网络结构、常用模型优化器、各种常用网络layer、多种模型训练技巧等； 3、熟悉至少一种计算机视觉任务，包括但不限于：图像分类、目标检测、目标跟踪、生物特征识别、关键点估计、ReID、动作识别等；4、熟练使用PyTorch、TensorFlow、Caffe等至少一种主流的深度学习训练框架；5、熟悉python、C/C++ 等至少一种编程语言 ；6、有人脸识别、行人和车辆重识别等成功项目经验，以及在视频分析算法，例如：视频分类/动作识别等方面，有相关研究经历或者项目经验优先考虑；7、具备良好的分析解决问题能力，优秀的学习能力，善于沟通和交流，有强烈的进取心、责任心和创新意识。以下为加分项：1、在CVPR、ICCV、ECCV、ICLR、AAAI、NeurlPS等高水平的会议或期刊发表过论文 ；2、在Kaggle、MS COCO等国内外知名算法竞赛中获得较好成绩；3、在知名科技公司、实验室、AI独角兽公司有实习经历； 投递...
The Role: Youll be an experienced real-time embedded system engineer with excellent knowledge in software build/test/release process for continuous integration and continuous deployment (CI/CD). Working in an agile cross-functional team, you will be a key member
Location:CN-Shenzhen-HyQ Shift:Standard - 40 Hours (China) Scheduled Weekly Hours:40 Worker Type:Permanent Job Summary:The purpose of this role is to support the matching engine technology team by contributing hands-on engineering capability and practical low latency expertise across
Our Journey The ShopBack Group is Asia-Pacific’s leading shopping, rewards, and payments platform, serving over 60 million shoppers across 13 markets. In 2025, the Group continued its global growth with its expansion into North America. Driven
Company: Qualcomm China Job Area:Engineering Group, Engineering Group Software Engineering General Summary: Job Overview Qualcomm is seeking a passionate and hands-on Camera AI Engineer to join our AI Software team in China. You will work with
Company: Qualcomm China Job Area:Engineering Group, Engineering Group Software Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of whats possible to enable next-generation experiences and drives digital transformation to help create a
Company: Qualcomm China Job Area:Engineering Group, Engineering Group Software Engineering General Summary: Develop and maintain the Qualcomm IOT Android platforms, co-work with global teams to provide the high-quality software for customers to support the success of
我们正在寻找一位 全栈工程师，参与核心 AI Agent 产品从架构设计、能力建设到生产落地的完整过程。你将参与 Web 产品、API 服务、Agent 编排系统、后台任务系统、数据层和部署流程等多个环节，和团队一起构建面向真实生产环境的 AI Agent 产品。 你将深度参与 AI Agent 系统的工程化建设，包括 Agent Loop、工具调用、任务编排、多步骤执行、上下文管理、模型路由、异步任务处理、结果持久化、错误恢复、日志追踪与系统可观测性等关键模块。这个岗位不是简单调用大模型 API，而是需要将 LLM 能力、业务流程、前后端系统和用户体验结合起来，构建可稳定运行、可持续扩展的生产级 Agent 产品。 在这个角色中，你需要理解 Agent 如何接收用户目标、拆解任务、选择工具、执行动作、处理中间状态、根据反馈继续推理，并最终产出可靠结果。你也需要关注 Agent 执行过程中的实际工程问题，例如任务超时、工具失败、重试策略、状态一致性、成本控制、并发执行、队列调度、数据追踪以及生成结果的可复现性。 你会和产品、设计、前端、后端和基础设施团队紧密协作，把 AI 能力落到真实的产品体验中。我们希望你既能理解前端产品形态和用户交互，也能深入后端服务、数据模型、任务队列和 Agent 编排系统，帮助团队搭建长期可维护、可扩展、可观测的 AI Agent 工程体系。
Purpose of Position The Data Analytics Engineer will be responsible for designing, building, and maintaining scalable analytics data solutions that support CASETiFY’s business intelligence, KPI reporting, dashboarding, and insight generation across the organization. The incumbent will
Flex is the diversified manufacturing partner of choice that helps market-leading brands design, build and deliver innovative products that improve the world. A career at Flex offers the opportunity to make a difference and invest in
Flex is the diversified manufacturing partner of choice that helps market-leading brands design, build and deliver innovative products that improve the world. A career at Flex offers the opportunity to make a difference and invest in
Location:CN-Shenzhen-HyQ Shift:Standard - 40 Hours (China) Scheduled Weekly Hours:40 Worker Type:Permanent Job Summary:Lead the design and delivery of LME market data platforms that consolidate multiple real-time and historical market data sources into scalable enterprise data assets
Location:CN-Shenzhen-HyQ Shift:Standard - 40 Hours (China) Scheduled Weekly Hours:40 Worker Type:Permanent Job Summary:Lead the design and delivery of LME market data platforms that consolidate multiple real-time and historical market data sources into scalable enterprise data assets
Who We Are Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our
Purpose of Position The Head of BI Analytics will be responsible for leading CASETiFY’s business intelligence and analytics capability, with a strong focus on data visualization, KPI setup, metadata establishment, and insight analysis across the organization.
Company Description WD is building the infrastructure behind the AI-driven data economy. As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time.
Company Description WD is building the infrastructure behind the AI-driven data economy. As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time.
About Wati Started as a WhatsApp team inbox in 2020, Wati has evolved into a full revenue orchestration system that goes beyond a single platform. We empower businesses that sell, support, and grow through conversations by
Wati Started as a WhatsApp team inbox in 2020, Wati has evolved into an AI-powered customer engagement platform that goes beyond a single channel. Designed for businesses that sell, support, and grow through conversations, Wati observes
我们正在寻找一位 全栈工程师，参与核心 AI Agent 产品从架构设计、能力建设到生产落地的完整过程。你将参与 Web 产品、API 服务、Agent 编排系统、后台任务系统、数据层和部署流程等多个环节，和团队一起构建面向真实生产环境的 AI Agent 产品。 你将深度参与 AI Agent 系统的工程化建设，包括 Agent Loop、工具调用、任务编排、多步骤执行、上下文管理、模型路由、异步任务处理、结果持久化、错误恢复、日志追踪与系统可观测性等关键模块。这个岗位不是简单调用大模型 API，而是需要将 LLM 能力、业务流程、前后端系统和用户体验结合起来，构建可稳定运行、可持续扩展的生产级 Agent 产品。 在这个角色中，你需要理解 Agent 如何接收用户目标、拆解任务、选择工具、执行动作、处理中间状态、根据反馈继续推理，并最终产出可靠结果。你也需要关注 Agent 执行过程中的实际工程问题，例如任务超时、工具失败、重试策略、状态一致性、成本控制、并发执行、队列调度、数据追踪以及生成结果的可复现性。 你会和产品、设计、前端、后端和基础设施团队紧密协作，把 AI 能力落到真实的产品体验中。我们希望你既能理解前端产品形态和用户交互，也能深入后端服务、数据模型、任务队列和 Agent 编排系统，帮助团队搭建长期可维护、可扩展、可观测的 AI Agent 工程体系。