蚂蚁金服蚂蚁国际-JAVA应用工程师-搜索
社招全职3年以上技术类-开发地点:深圳状态:招聘
任职要求
1、精通Java,3年以上大规模搜索系统开发经验,主导过索引架构、分布式检索、高并发服务等模块设计。 2、熟悉向量数据库(如Milvus)、流式计算(Flink)、批量计算(spark) 等技术。 3、对搜索技术有极致追求,善于通过AB实验、用户反馈等闭环驱动技术迭代。 4、熟悉分布式系统的设计和应用,熟悉分布式、缓存、消息等机制;能对分布式常用技术进行合理应用,解决问题; 5、有钱包综合性搜索经验的优先 6、学习能力强,优秀的沟通表达能力和跨团队协同能力,具备英语交流能力以及英文文档的编写阅读能力和团队协作精神;
工作职责
1、主导钱包搜索全链路技术,包括搜索建议,Query理解、粗排,精排、干预等环节的工程优化,能和算法一起提升搜索效果。 2、设计高可靠、高扩展的搜索架构,主导大数据量的数据索引、向量检索、分布式实时计算等系统的研发与优化。 3、各种离线挖掘工作,包括同义词,知识图谱等 4、持续全链路性能优化,实现低延迟、高吞吐的搜索服务,支撑万级QPS场景。 5、理解和掌握蚂蚁集团的常用架构设计、性能优化、高可用保障理念,并能灵活运用于核心链路系统的优化;
包括英文材料
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
高并发+
https://www.baeldung.com/concurrency-principles-patterns
In this tutorial, we’ll discuss some of the design principles and patterns that have been established over time to build highly concurrent applications.
https://www.baeldung.com/java-concurrency
Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.
https://www.oreilly.com/library/view/concurrency-in-go/9781491941294/
You’ll understand how Go chooses to model concurrency, what issues arise from this model, and how you can compose primitives within this model to solve problems.
https://www.oreilly.com/library/view/modern-concurrency-in/9781098165406/
With this book, you'll explore the transformative world of Java 21's key feature: virtual threads.
https://www.youtube.com/watch?v=qyM8Pi1KiiM
https://www.youtube.com/watch?v=wEsPL50Uiyo
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
分布式系统+
https://www.distributedsystemscourse.com/
The home page of a free online class in distributed systems.
https://www.youtube.com/watch?v=7VbL89mKK3M&list=PLOE1GTZ5ouRPbpTnrZ3Wqjamfwn_Q5Y9A
缓存+
https://hackernoon.com/the-system-design-cheat-sheet-cache
The cache is a layer that stores a subset of data, typically the most frequently accessed or essential information, in a location quicker to access than its primary storage location.
https://www.youtube.com/watch?v=bP4BeUjNkXc
Caching strategies, Distributed Caching, Eviction Policies, Write-Through Cache and Least Recently Used (LRU) cache are all important terms when it comes to designing an efficient system with a caching layer.
https://www.youtube.com/watch?v=dGAgxozNWFE
相关职位
社招TPG
-负责搜索服务架构建设,支持企业内部各类搜索系统的架构研发工作; -负责服务治理与重构、云原生架构改造、搜索性能优化,保证搜索系统的可扩展性与可持续发展; -负责智能化语义检索,机器学习与大模型技术在搜索场景的应用落地,提升搜索的智能化水平; -支持用户体验、内容生态的革新;
更新于 2025-06-12
校招智能信息秋季20
阿里巴巴智能信息事业群,聚焦AI在信息服务赛道的创新应用,从工具到服务,持续为用户提供高效、智能的AI应用。智能信息事业群核心产品为夸克、通义、UC浏览器、书旗小说、超级汇川等,以多产品矩阵,覆盖横跨各年龄段的7亿+用户人群,服务超10万+客户。 1、参与并负责核心内容场景的各类算法,包括AI个性化推荐系统、内容生态构建、内容理解等核心算法能力; 2、深度参与内容分发算法设计,提升流量匹配的效率和用户粘性; 3、建设包括AGENT、RAG、召回、粗排、精排、重排、混排等搜索和推荐模块,打造集团和业界一流的内容算法; 4、参与设计多模态内容理解和推荐分发系统,推动解决内容的一致性和标准化问题。
更新于 2025-08-13
社招3年以上核心本地商业-点
1.负责点评搜索核心服务的架构抽象和优化,高效支持数据接入、召回、排序、展示等功能,支持搜索相关工具建设与优化,提升工程、算法、产品的迭代效率; 2.通过合理的技术选型和实现,保障搜索系统的高可用、高吞吐、低延迟; 3.深入理解搜索业务和产品需求,从而抽象出系统模型,高效支持点评App搜索需求研发工作。
更新于 2025-04-23