京东AIOps算法工程师
社招全职算法开发岗地点：上海状态：招聘
任职要求
1. 硕士及以上学历，计算机科学或相关STEM领域专业背景，具备扎实编码能力（python/java）； 2. 熟练掌握机器学习/数据挖掘/自然语言处理（LLM/Agent/RAG）等相关领域的理论和算法； 3. 具备良好的分析和问题解决能力、优秀的工程素养，能够独立思考和解决实际问题； 4. 熟练使用深度学习框架PyTorch/TensorFlow或者大数据框架Spark/Flink者优先； 5. 在机器学习、数据挖掘、软件工程CCF-A/B类会议有相关论文发表者优先； 6. 参加过KDDCup/Kaggle/AIOps Challenge等相关比赛并取得好成绩者优先。 符合京东价值观：客户为先、创新、拼搏、担当、感恩、诚信。
工作职责
1. 与业务/工程/产品团队配合，面向京东零售业务系统和基础设施高可用需求以及海量数据，参与智能运维系统规划和设计； 2. 深入京东零售智能运维具体场景，包括但不限于软件变更、性能容量、监控告警、应急定位、资金核对、客诉舆情、工单处置等场景，面向实际问题，研发机器学习算法，沉淀平台能力； 3. 跟踪和研究前沿智能运维、机器学习、大模型/智能体等技术方向，推动相关领域技术创新，助力京东业务系统高可靠性。
包括英文材料
学历+
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.
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.
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
数据挖掘+
https://www.youtube.com/watch?v=-bSkREem8dM
Database vs Data Warehouse vs Data Lake
https://www.youtube.com/watch?v=7rs0i-9nOjo
NLP+
https://www.youtube.com/watch?v=fNxaJsNG3-s&list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S
Welcome to Zero to Hero for Natural Language Processing using TensorFlow!
https://www.youtube.com/watch?v=R-AG4-qZs1A&list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Natural Language Processing tutorial for beginners series in Python.
https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4
The foundations of the effective modern methods for deep learning applied to NLP.
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
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
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/
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具，在灵活性、可读性和性能上都具备相当的优势，近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
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.
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.
Kaggle+
[英文] Kaggle Learn
https://www.kaggle.com/learn
Gain the skills you need to do independent data science projects.
相关职位
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团队介绍：字节跳动APM（Application Performance Management）团队负责全栈产品（服务端、移动端、前端、跨端）的稳定性与性能质量监控，构建业界领先的可观测性基础设施。团队提供一站式观测平台，满足公司各业务线故障排查、监控及各类稳定性需求。 1、AIOps技术深化：AIOps智能运维方向通过融合统计、机器学习和LLM各类算法，实现智能报警、根因定位等；负责主导时序分析、故障诊断、根因关联推断及日志聚类等算法设计； 2、前沿技术创新应用：负责探索LLM Agent在可观测性、自动化运维中落地应用； 3、算法平台与解决方案落地：负责算法解决方案及平台全流程设计，支持算法应用。
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社招2年以上技术类
1、负责AIOps领域算法设计实现,包括时序分析、日志挖掘、故障预测、根因关联推断和智能决策等;2、探索AIOps的落地应用,包括但不限于异常检测、根因定位、咨询服务等场景;3、跟进可观测领域前沿技术、开源方案及其在AIOps领域的应用。
更新于 2025-08-27
社招A142310
1、面向应用发布和线上变更，进行风险防控相关的流程规范，服务化和能力化建设，支撑业务变更过程有效风险发现与高危熔断； 2、面向大型业务运营活动提供稳定性保障能力，包含而不限于服务压测，容量评估，混沌验证，红蓝攻防开展等，支撑业务高可用水位持续提升； 3、采用统计分析、机器学习和人工智能算法，解决场景目标中的各类预测评估问题， 围绕评估，预测，归因，自愈四大维度，推进AIOps体系持续完善。
更新于 2024-06-21