百度大数据引擎研发工程师(J91579)
社招全职ACG地点:北京状态:招聘
任职要求
-本科及以上学历,计算机或相关专业 -扎实的Java/Scala/Python编程能力,熟悉多线程、JVM调优及分布式系统设计 -精通Ray、Spark等引擎,并具备底层实现理解及控制优化能力 -大数据开源组件源码,大模型相关经验优先(如LLM数据处理,RAG应用) -对技术充满热情,具备敏锐的数据思维和敏知力,工作计划性强,执行力出众,责任心强
工作职责
-参与AI数据处理产品和引擎的研发与优化 -构建高可靠、高性能的分布式数据处理系统,支持EB级数据计算 -设计并优化数据库仓库及数据湖架构,实现流批一体、CPU/GPU混合负载计算性能的优化 -探索大数据与AI的创新结合与应用
包括英文材料
学历+
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.
Scala+
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.
多线程+
https://liaoxuefeng.com/books/java/threading/basic/index.html
和单线程相比,多线程编程的特点在于:多线程经常需要读写共享数据,并且需要同步。
https://www.youtube.com/watch?v=_uQgGS_VIXM&list=PLsc-VaxfZl4do3Etp_xQ0aQBoC-x5BIgJ
https://www.youtube.com/watch?v=IEEhzQoKtQU
https://www.youtube.com/watch?v=mTGdtC9f4EU&list=PLL8woMHwr36EDxjUoCzboZjedsnhLP1j4
https://www.youtube.com/watch?v=TPVH_coGAQs&list=PLk6CEY9XxSIAeK-EAh3hB4fgNvYkYmghp
https://www.youtube.com/watch?v=xPqnoB2hjjA
This video is an introduction to multithreading in modern C++.
https://www.youtube.com/watch?v=YKBwKy5PrpQ
Rust threading is easy to implement and improves the efficiency of your applications on multi-core systems!
JVM+
https://www.freecodecamp.org/news/jvm-tutorial-java-virtual-machine-architecture-explained-for-beginners/
https://www.youtube.com/watch?v=e2zmmkc5xI0
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
Ray+
https://github.com/ray-project/ray
Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
https://www.youtube.com/watch?v=FhXfEXUUQp0
In this video, I'll teach you everything you need to know about Apache Ray!
https://www.youtube.com/watch?v=fMiAyj2kgac
Using powerful machine learning algorithms is easy using Ray.io and Python.
https://www.youtube.com/watch?v=q_aTbb7XeL4
Parallel and Distributed computing sounds scary until you try this fantastic Python library.
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.
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.
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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1、参与快手EB级大数据平台分布式计算引擎相关系统的研发与优化工作,解决实际业务需求与性能问题。子系统包括但不限于Hive、Spark,Presto、Flink、Druid、Clickhouse等; 2、接受大数据平台系统设计与实现复杂度的挑战,分析和发现系统的优化点,负责推动系统的合理性、可靠性、可用性的提升; 3、和开源社区保持交流,从社区引入对公司业务场景有帮助的特性与系统,或将内部研发的功能贡献到社区。
更新于 2025-07-30
社招D7195
1、参与快手EB级大数据平台计算引擎相关系统的研发与优化工作,解决实际业务需求与性能问题; 2、接受大数据平台系统设计与实现复杂度的挑战,分析和发现系统的优化点,负责推动系统的合理性、可靠性、可用性的提升; 3、和开源社区保持交流,从社区引入对公司业务场景有帮助的特性与系统,或将内部研发的功能贡献到社区。
更新于 2025-03-07
社招D7195
1、参与快手EB级大数据平台计算引擎相关系统的研发与优化工作,解决实际业务需求与性能问题; 2、接受大数据平台系统设计与实现复杂度的挑战,分析和发现系统的优化点,负责推动系统的合理性、可靠性、可用性的提升; 3、和开源社区保持交流,从社区引入对公司业务场景有帮助的特性与系统,或将内部研发的功能贡献到社区。
更新于 2025-03-07