
智能互联阿里云智能-技术服务经理TAM-公共云互联网KA客户-北京
社招全职2年以上地点:北京状态:招聘
工作描述
任职要求 1. 2年以上泛娱乐、零售、金融、教育等行业大型互联网应用(含AI原生应用)或集团型企业应用的研发、架构设计、监控方案、Devops、AIops、维护、高可用改造方案经验。 2. 熟悉Agent开发框架及工具(LangChain/Dify/LlamaIndex/百炼等),模型推理框架(vLLM /sglang),模型训练框架(LlamaFactory、swift等),具备GPU集群调度、资源隔离、显存优化相关经验,能够解决大规模算力下的性能瓶颈与稳定性问题。 3. 熟悉主流大模型推理框架(如 vLLM, Triton Inference Server, TensorRT-LLM, TGI 等)。 4. 了解 NVIDIA GPU 底层架构及分布式通信机制(如 NVLink, NCCL, RDMA/RoCE 高速网络)。 5. 熟悉JAVA、Python、GO其中一门开发语言,熟悉常见中间件、数据库、大数据组件,如Redis、Nacos、K8s、Kafka、spark、flink等,具有2年以上软件开发经验优先。 6. 具备大模型、云原生、大数据、数据库、网络、中间件等领域中的一项或多项技术理解和应用经验,有阿里云公共云产品相关使用运维经验优先。 7. 熟悉云原生的系统架构…
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包括英文材料
系统设计+
https://roadmap.sh/system-design
Everything you need to know about designing large scale systems.
https://www.youtube.com/watch?v=F2FmTdLtb_4
This complete system design tutorial covers scalability, reliability, data handling, and high-level architecture with clear explanations, real-world examples, and practical strategies.
DevOps+
https://roadmap.sh/devops
Step by step guide for DevOps, SRE or any other Operations Role in 2025
https://zhuanlan.zhihu.com/p/562036793
DevOps中的Dev指的是Development(开发),Ops指的是Operations(运维),用一句话来说,DevOps就是打通开发运维的壁垒,实现开发运维一体化。
高可用+
https://redis.io/blog/high-availability-architecture/
A high available architecture is when there are a number of different components, modules, or services that work together to maintain optimal performance, irrespective of peak-time loads.
https://www.ibm.com/think/topics/high-availability
High availability (HA) is a term that refers to a system’s ability to be accessible and reliable close to 100% of the time.
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.
开发框架+
[英文] Understanding Modern Development Frameworks: A Guide for Developers and Technical Decision-makers
https://www.freecodecamp.org/news/understanding-modern-development-frameworks-guide-for-devs/
LangChain+
https://python.langchain.com/docs/tutorials/
New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications.
https://www.freecodecamp.org/news/beginners-guide-to-langchain/
LangChain is a popular framework for creating LLM-powered apps.
LlamaIndex+
https://developers.llamaindex.ai/python/framework/getting_started/starter_example/
This tutorial will show you how to get started building agents with LlamaIndex.
https://www.ibm.com/think/tutorials/llamaindex-rag
LlamaIndex is a powerful open source framework that simplifies the process of building RAG pipelines.
vLLM+
https://www.newline.co/@zaoyang/ultimate-guide-to-vllm--aad8b65d
vLLM is a framework designed to make large language models faster, more efficient, and better suited for production environments.
https://www.youtube.com/watch?v=Ju2FrqIrdx0
vLLM is a cutting-edge serving engine designed for large language models (LLMs), offering unparalleled performance and efficiency for AI-driven applications.
SGLang+
[英文] Install SGLang
https://docs.sglang.ai/get_started/install.html
SGLang is a fast serving framework for large language models and vision language models.
https://github.com/sgl-project/sgl-learning-materials
Swift+
[英文] A Swift Tour
https://docs.swift.org/swift-book/documentation/the-swift-programming-language/guidedtour/
Explore the features and syntax of Swift.
https://www.hackingwithswift.com/learn
Free Swift and iOS tutorials
https://www.youtube.com/watch?v=8Xg7E9shq0U
Learn the Swift programming language in this full tutorial for beginners.
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
Triton Inference Server+
https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/index.html
Triton Inference Server is an open source inference serving software that streamlines AI inferencing.
TensorRT+
https://docs.nvidia.com/deeplearning/tensorrt/latest/getting-started/quick-start-guide.html
This TensorRT Quick Start Guide is a starting point for developers who want to try out the TensorRT SDK; specifically, it demonstrates how to quickly construct an application to run inference on a TensorRT engine.
TGI+
https://huggingface.co/docs/text-generation-inference/en/index
Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs).
https://learn.ritual.net/examples/tgi_inference_with_mistral_7b
In this tutorial, we will use Huggingface's TGI (Text Generation Interface) API to query a Large Language Model (LLM) and enable users to requests jobs from it, both on-chain and off-chain.
https://www.sandgarden.com/learn/text-generation-inference-tgi
Text Generation Inference (TGI) is the process by which a trained AI model generates new text based on an input prompt, focusing on producing this text efficiently in terms of speed and computational resources.
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