58同城后端开发工程师-推荐工程(J34892)
社招全职2年以上技术类地点:北京状态:招聘
任职要求
1、计算机相关专业本科及以上学历,2 年以上后端开发经验,具备扎实的工程素养与规范的编码习惯,能独立主导复杂模块的设计与实现; 2、精通 Java/Python/C++ 中至少一种编程语言,深入理解分布式系统原理;熟练掌握 Spark、Hive 等大数据处理工具,具备大规模数据清洗、特征工程实践经验; 3、深入理解 Elasticsearch、Faiss 等检索引擎的底层原理与调优方法,有实际检索系统搭建或优化经验; 4、熟悉 Flink 等流处理框架、Redis 缓存机制、MySQL 索引优化者优先,具备高并发场景下服务性能调优经验者优先; 5、对搜索推荐系统架构有深刻理解,熟悉召回 - 排序全链路工程化方案,有实际搜推系统迭代或效果优化案例者优先; 6、具备技术前瞻性,主动关注大模型、RAG 等前沿技术,有相关技术在业务场景落地经验者优先; 7、具备优秀的问题分析与解决能力,良好的跨团队沟通协作意识,能在复杂业务场景中推动技术方案落地。 我们期望你 对技术有高追求,既能沉下心打磨服务细节,也能跳脱出业务框架探索创新方向;乐于分享与协作,通过技术影响力带动团队共同成长。
工作职责
职位定位 负责搜索推荐场景下算法服务的后端架构设计、工程化落地及技术创新,通过高效的数据处理与服务架构支撑,推动业务指标持续优化,同时探索大模型、RAG 等前沿技术在搜推领域的规模化应用。 核心职责: 1、主导搜索推荐算法服务的后端架构设计与演进,负责高可用、高并发服务的开发、部署及全生命周期维护,保障服务性能与稳定性; 2、设计并优化后端数据服务框架,支撑大规模用户行为数据、物品特征数据的高效处理与流转,提升数据链路的可靠性与实时性; 3、牵头探索大模型、RAG 等新技术在搜推场景的落地路径,主导技术方案设计、原型验证及工程化实现,持续优化检索精度与推荐效果; 4、与算法团队、产品团队深度协同,通过技术手段解决算法落地中的工程瓶颈(如响应延迟、资源消耗、离线 / 在线一致性等),推动线上核心指标(CTR、CVR、用户留存等)提升; 5、负责技术选型与技术债务治理,制定服务性能基准与优化策略,推动团队工程实践标准化。
包括英文材料
学历+
后端开发+
https://www.youtube.com/watch?v=tN6oJu2DqCM&list=PLWKjhJtqVAbn21gs5UnLhCQ82f923WCgM
Learn what technologies you should learn first to become a back end web developer.
编程规范+
[英文] Google Style Guides
https://google.github.io/styleguide/
Every major open-source project has its own style guide: a set of conventions (sometimes arbitrary) about how to write code for that project. It is much easier to understand a large codebase when all the code in it is in a consistent style.
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.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
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
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.
Hive+
[英文] Hive Tutorial
https://www.tutorialspoint.com/hive/index.htm
Hive is a data warehouse infrastructure tool to process structured data in Hadoop. It resides on top of Hadoop to summarize Big Data, and makes querying and analyzing easy.
https://www.youtube.com/watch?v=D4HqQ8-Ja9Y
特征工程+
https://www.ibm.com/think/topics/feature-engineering
Feature engineering preprocesses raw data into a machine-readable format. It optimizes ML model performance by transforming and selecting relevant features.
https://www.kaggle.com/learn/feature-engineering
Better features make better models. Discover how to get the most out of your data.
ElasticSearch+
https://www.youtube.com/watch?v=a4HBKEda_F8
Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations.
Faiss+
https://faiss.ai/index.html
Faiss is a library for efficient similarity search and clustering of dense vectors.
https://huggingface.co/learn/llm-course/en/chapter5/6
In this section we’ll use this information to build a search engine that can help us find answers to our most pressing questions about the library!
信息检索+
https://nlp.stanford.edu/IR-book/information-retrieval-book.html
Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.
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.
Redis+
[英文] Developer Hub
https://redis.io/dev/
Get all the tutorials, learning paths, and more you need to start building—fast.
https://www.runoob.com/redis/redis-tutorial.html
REmote DIctionary Server(Redis) 是一个由 Salvatore Sanfilippo 写的 key-value 存储系统,是跨平台的非关系型数据库。
https://www.youtube.com/watch?v=jgpVdJB2sKQ
In this video I will be covering Redis in depth from how to install it, what commands you can use, all the way to how to use it in a real world project.
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
MySQL+
https://juejin.cn/post/7190306988939542585
这是一篇 MySQL 通关一篇过硬核经验学习路线,包括数据库相关知识,SQL语句的使用,数据库约束,设计等。
[英文] MySQL Tutorial
https://www.mysqltutorial.org/
your go-to resource for mastering MySQL in a fast, easy, and enjoyable way.
https://www.youtube.com/watch?v=5OdVJbNCSso
MySQL SQL tutorial for beginners
https://www.youtube.com/watch?v=7S_tz1z_5bA
This beginner-friendly course teaches you SQL from scratch.
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
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.
推荐系统+
[英文] Recommender Systems
https://www.d2l.ai/chapter_recommender-systems/index.html
Recommender systems are widely employed in industry and are ubiquitous in our daily lives.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
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