About our group: The Intelligent Engineering & Enterprise Systems (IEES) organization provides and supports the digital platforms that enable Seagates global engineering teams to develop industry-leading storage products. Our team manages Product Lifecycle Management (PLM), Engineering Knowledge Management, JIRA
Who we are looking for State Street Investment Management (SSIM)—formerly State Street Global Advisors (SSGA)—is seeking an accomplished senior leader to serve as the Global Head of Analytics and AI Platform Engineering. This Managing Director role is critical
Some careers have more impact than others. If you’re looking for a career where you can make a real impression, join HSBC and discover how valued you’ll be. We are currently seeking an experienced professional to
Some careers have more impact than others. If you’re looking for a career where you can make a real impression, join HSBC and discover how valued you’ll be. We are currently seeking an experienced professional to
About our group: Our GFIT Software Development team in Wuxi supports Seagate’s factory digital transformation by delivering MES-related applications, manufacturing software, data solutions, and automation capabilities for real production operations. We focus on applying AI, GenAI, analytics,
AI Platform Engineer – SA Role Summary Design, build, and run core services and reusable components for the open-architecture AI platforms, enabling scalable ingestion, metadata-driven processing, governance, and reliable workflow automation. Deliver production-grade capabilities supporting agentic AI solutions Key
About our group: Operations Excellence department is responsible for site productivity improvement, planning and allocating manufacturing specialist resources, managing budgets and procurement of indirect materials, training production-related personnel, and fostering a culture of continuous improvement. Additionally,
ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them
AI数据产品经理 北京 社招 全职 职位 ID：A229708 职位描述 核心职责1.产品规划与设计：负责 Data Agent 产品整体规划，制定产品路线图（P0智能查数 → P1自动诊断 → P2智能洞察 → P3闭环自治），输出高质量 PRD。2.AI Agent 产品定义：设计五大 Agent（意图识别/查询/分析/预警/洞察）的能力边界、交互流程与协作机制。3.NL2SQL 体验优化：持续优化自然语言到SQL的转换准确率（目标≥90%），设计指标语义映射、上下文补全、多轮追问等核心体验。4.用户场景落地：深入业务一线，将智能取数、自动报表、根因诊断、趋势预测、异常告警等场景打磨为可用产品。5.数据资产治理：参与 Ontology体系建设，推动指标口径标准化、知识图谱构建，为 Agent 提供高质量语义基座。6.跨团队协同：对接算法、研发、数据分析团队，确保产品方案高效落地；与业务方保持紧密沟通，验证产品价值。延伸职责1.竞品分析：跟踪业界 AI+数据分析产品动态（如 ThoughtSpot、Databricks AI/BI、阿里 DataAgent 等）。2.效果度量：建立产品效果评估体系（准确率、响应时间、用户满意度、取数替代率等）。3.内部推广：推动产品在业务团队的试用与推广，收集反馈迭代。 职位要求 1.3-5年产品经理经验，其中至少 2年数据产品/BI/数据平台 相关经验。2.熟悉数据仓库体系（维度建模、指标体系），能写 SQL，理解 ETL 流程。3.了解 LLM 基本原理与能力边界，理解
AI数据产品经理 北京 社招 全职 职位 ID：A86598 职位描述 1.Data Agent 产品规划与设计：负责智能分析平台整体规划及落地2.龙虾运营看板产品设计：与数据研发协作，完善使用/体验/成本/Skill 四块看板，建立任务质量分级体系（L1-L4）、留存粘性指标、ROI 衡量模型3.指标口径治理：主导 Ontology 体系建设，推动指标定义标准化，确保 Agent 和看板使用统一语义4.数据质量闭环：数据治理及数据监控数据异常艰苦及分析，推动问题从发现→归因→修复→验证全流程闭环5.NL2SQL 体验优化：优化自然语言取数准确率（目标 ≥90%），设计多轮追问、上下文补全、指标语义映射等核心体验6.跨团队协同：对接算法（Agent 编排）、研发（平台开发）、数据团队（数仓/ETL）、业务方（需求验证），确保方案高效落地 职位要求 1.经验：3-5 年产品经理经验，其中至少 2 年数据产品/BI/数据平台相关经验2.数据基础：熟悉数据仓库体系（维度建模、指标体系），能写 SQL，理解 ETL 流程3.AI 认知：了解 LLM 基本原理与能力边界，理解 Prompt Engineering、RAG、Agent 编排等概念4.产品能力：优秀的需求分析与 PRD 撰写能力，能独立完成从 0 到 1 的产品设计5.沟通力：出色的跨团队沟通协调能力，能与算法/研发/数据团队高效对话
AI属性工程师 南京 社招 全职 职位 ID：A250806 职位描述 负责将大模型、智能体等AI能力落地至整车研发流程，提升工程团队研发效率。具体包括：1）基于业务场景构建AI Agent，实现重复性工作的自动化接管；2）针对不同工程领域定制Prompt模板，建设可复用的Skills库；3）维护部门级AI中台底座，保障AI工具链的稳定性与持续迭代；4）识别高频事务性工作，设计并开发自动化工作流 职位要求 1. 本科及以上学历，计算机科学、人工智能、软件工程等相关专业；2. 2-3年AI应用开发经验，熟练掌握Python开发；3. 具备LLM应用开发实战经验，熟悉Prompt Engineering、Agent框架、RAG技术；4. 理解工程业务流程，能够将业务需求转化为技术方案；5. 具备数据处理与分析能力，包括数据清洗、可视化、报表生成；6. 具备快速学习能力，能跟进AI前沿技术并评估落地可行性 投递...
Are you ready to shape a better tomorrow? AIA Digital+ is a Technology, Digital and Analytics innovation hub dedicated to powering AIA to be more efficient, connected and innovative as it fulfils its Purpose to help
Work Your Magic with us! Ready to explore, break barriers, and discover more? We know you’ve got big plans – so do we! Our colleagues across the globe love innovating with science and technology to enrich
Requisition Number: 75402 The company built on breakthroughs. Join us. Corning is one of the world’s leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space,
Amazon Private Brands Product Quality team is looking for a smart, hard-working and creative member for our Shenzhen office. The successful candidate will show excellent judgment and instincts in decision making and proactively and continually improve
Job Description:Essential Job Functions:•Contribute to software development projects by writing, testing, and debugging code, with an emphasis on complex and critical components.•Collaborate with team members to meet project requirements, actively participating in design and code reviews.•Provide
Are you ready to shape a better tomorrow? AIA Digital+ is a Technology, Digital and Analytics innovation hub dedicated to powering AIA to be more efficient, connected and innovative as it fulfils its Purpose to help
Provides technical leadership and drives consistency, integrity, and technical quality in the execution of testing performed by staff located at all UL Solutions Laboratories. Is the global technical expert for the assigned skill set(s), including complex
AI Agent 算法实习生 上海 实习 数字技术 职位 ID：A245234A 职位描述 1. AI Agent 策略设计与研发： 基于开源的AI Agent框架（如openclaw、nanoclaw），负责 Agent 的核心逻辑设计与链路编排。针对外部数据抓取与内部业务数据检索，设计高效的意图识别与数据提取策略。2. 大模型自动化内容生成： 针对微信公众号、微博、小红书等多平台的内容生态，研发并优化基于 LLM 的自动化运营策略，通过 Prompt Engineering 提升图文生成的质量、相关性与转化率。3. 大模型应用落地与工程化： 参与各类 AI 产品与飞书办公生态的深度集成，协助完成阶段性 Demo 的算法效果验证与功能验收，确保模型在真实场景下的稳定性与准确性。4. 前沿技术追踪与预研： 持续关注并追踪 LLM、Agentic Workflow、RAG 等领域的最新学术进展与开源社区动态，配合团队完成新技术在具体业务场景（如自动化数据收集、内容营销、销售管理）下的可行性验证。 职位要求 1. 计算机、人工智能、数据科学等相关专业本科及以上学历，在校生。2. 具备扎实的算法基础（机器学习/NLP优先），熟练掌握 Python，具备良好的代码习惯。3. 熟悉当前主流大模型的
端侧 AI 部署与应用工程师 (2026届校招) 北京 校招 正式 智能制造 / 工业互联网 / 工业自动化 - 研发 职位描述 你将加入我们的核心研发团队，基于Qualcomm计算平台，打通从 AI 模型到端侧应用落地的“最后一公里”。我们需要你不仅懂算法原理，更能通过扎实的工程能力，构建高性能的 AI Agent 与推理系统。1. 模型转换与性能调优 (Model Engineering):使用 Linux 环境下的工具链，将 PyTorch/TensorFlow 训练模型转换为专用格式（DLC/QNN context）。编写 Shell/Python 脚本 实现模型转换、量化（Int8/FP16）及精度验证的自动化流程。分析模型在 Hexagon DSP/NPU 上的性能瓶颈，进行算子优化和推理加速。2. 端侧 AI 系统开发 (System Integration):基于 Android/Linux