小红书生态研发工程师-社区治理
社招全职3-5年引擎地点：北京 | 上海 | 杭州状态：招聘
任职要求
1. 本科及以上学历，计算机科学、软件工程或相关专业，至少3年分布式系统开发经验。 2. 具备扎实的Java编程基础，精通Java集合框架，深刻理解分布式存储、计算、消息队列（如Kafka/RocketMQ）、微服务治理等核心技术原理与应用。 3. 拥有丰富的线上系统稳定性保障和性能调优经验，具备复杂生产环境下的快速故障定位（trouble-shooting）和解决能力。 4. 具备大数据平台研发经验，熟练掌握并应用Spark、Hadoop、Flink等主流大数据处理技术栈。 5. 具备良好的数据敏感度和逻辑分析能力，能够进行深层次的数据探查和业务问题分析，对业务风险有较强的洞察力（业务sense）；有数据分析或算法模型落地经验者优先。 6. 拥有内容安全、风险控制、反作弊等相关领域业务经验者优先考虑。 7. 优秀的沟通协作能力和责任心，能够积极主动地推动项目进展和解决复杂问题。 8. 具备较强的学习能力和技术热情，能快速适应业务需求和技术变化。
工作职责
1. 负责风控后端审核系统（人工/机器）及引擎的架构设计与优化，解决核心系统的性能瓶颈、架构演进问题，并保障线上系统的稳定性和高可用性。 2. 负责内容安全模型平台的功能开发与系统稳定性保障，进行高质量的系统设计与实现，支撑亿级日活（DAU）产品的数据流处理、运营系统、审核系统等核心平台的建设与维护。 3. 参与大规模机器学习在线推理框架的研发、优化与维护，确保模型高效、稳定地服务于线上业务。 4. 持续优化在线服务与离线计算任务的性能，设计并实施高并发、多机房部署、容灾备份等关键方案，保障系统弹性与业务连续性。 5. 参与风控策略的技术实现与落地，为策略迭代提供高效、可靠的技术支持。 6. 关注技术前沿，参与技术选型与架构演进，推动风控技术栈的持续升级。 7. 协同风控策略、算法、数据、产品及运营团队，高效沟通，共同达成业务目标。
包括英文材料
学历+
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
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.
消息队列+
https://www.youtube.com/watch?v=xErwDaOc-Gs
Kafka+
https://developer.confluent.io/what-is-apache-kafka/
https://www.youtube.com/watch?v=CU44hKLMg7k
https://www.youtube.com/watch?v=j4bqyAMMb7o&list=PLa7VYi0yPIH0KbnJQcMv5N9iW8HkZHztH
In this Apache Kafka fundamentals course, we introduce you to the basic Apache Kafka elements and APIs, as well as the broader Kafka ecosystem.
RocketMQ+
https://www.baeldung.com/apache-rocketmq-spring-boot
In this tutorial, we’ll create a message producer and consumer using Spring Boot and Apache RocketMQ, an open-source distributed messaging and streaming data platform.
微服务+
https://learn.microsoft.com/en-us/training/modules/dotnet-microservices/
Microservice applications are composed of small, independently versioned, and scalable customer-focused services that communicate with each other by using standard protocols and well-defined interfaces.
https://microservices.io/
Microservices - also known as the microservice architecture - is an architectural style that structures an application as a collection of two or more services.
https://spring.io/microservices
Building small, self-contained, ready to run applications can bring great flexibility and added resilience to your code.
https://www.ibm.com/think/topics/microservices
Microservices, or microservices architecture, is a cloud-native architectural approach in which a single application is composed of many loosely coupled and independently deployable smaller components or services.
https://www.youtube.com/watch?v=CqCDOosvZIk
https://www.youtube.com/watch?v=hmkF77F9TLw
Learn about software system design and microservices.
性能调优+
https://goperf.dev/
The Go App Optimization Guide is a series of in-depth, technical articles for developers who want to get more performance out of their Go code without relying on guesswork or cargo cult patterns.
https://web.dev/learn/performance
This course is designed for those new to web performance, a vital aspect of the user experience.
https://www.ibm.com/think/insights/application-performance-optimization
Application performance is not just a simple concern for most organizations; it’s a critical factor in their business’s success.
https://www.oreilly.com/library/view/optimizing-java/9781492039259/
Performance tuning is an experimental science, but that doesn’t mean engineers should resort to guesswork and folklore to get the job done.
大数据+
https://www.youtube.com/watch?v=bAyrObl7TYE
https://www.youtube.com/watch?v=H4bf_uuMC-g
With all this talk of Big Data, we got Rebecca Tickle to explain just what makes data into Big Data.
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.
Hadoop+
https://www.runoob.com/w3cnote/hadoop-tutorial.html
Hadoop 为庞大的计算机集群提供可靠的、可伸缩的应用层计算和存储支持，它允许使用简单的编程模型跨计算机群集分布式处理大型数据集，并且支持在单台计算机到几千台计算机之间进行扩展。
[英文] Hadoop Tutorial
https://www.tutorialspoint.com/hadoop/index.htm
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models.
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.
数据分析+
[英文] Data Analyst Roadmap
https://roadmap.sh/data-analyst
Step by step guide to becoming an Data Analyst in 2025
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
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