阿里巴巴AI Infra网络研发工程师
实习兼职阿里巴巴2027届实习生地点:北京 | 杭州状态:招聘
工作描述
任职要求 1. AI通用能力: ● 系统思维:具备独立思考分析与系统化解决问题能力,喜欢从底层视角拆解问题,能够从 0 到 1 推进复杂项目落地 ● 沟通协作:有良好的沟通协作与跨团队推动能力,能够与产品、业务、硬件、算法等多方高效协同 ● 探索热情:对网络系统和 AI 技术持续保持好奇心和创新精神,对于技术突破充满热情,自驱力和学习力强,有意愿在该领域长期深耕 ● 乐观抗压:喜欢挑战性的技术研发工作,善于攻坚克难,积极乐观,坚韧抗压,结果导向 2. AI技能: ● AI基础设施与框架理解:深入理解主流AI框架(PyTorch/TensorFlow)的底层通信机制,熟悉集合通信库(NCCL)的工作原理,能够针对AI训练和推理场景进行网络层面的适配与调优。 ● 大模型推理系统优化:掌握大模型推理的核心技术,理解分布式推理中的张量并行、流水线并行对网络带宽和延迟的具体需求,熟悉KV Cache远端访问等显存优化技术对网络I/O的影响。 ● Agentic应用支持能力:理解AI Agent的运行逻辑,包括工具调用、沙箱环境构建及多轮对话状态管理,能够针对Agent的动态交互特性设计相应的网络接入与流量调度策略。 ● AI网络性能分析:熟练使用各类性能分析工具,能够对AI工作负载下的网络流量进行抓包分析与建模,识别计算与通信重叠(Overlap)中的瓶颈。 3. 专业领域: ● 高性能网络架构设计…
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包括英文材料
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/
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.
NCCL+
https://developer.nvidia.com/nccl
The NVIDIA Collective Communication Library (NCCL) implements multi-GPU and multi-node communication primitives optimized for NVIDIA GPUs and networking.
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
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
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.
流量调度+
https://ferrishall.dev/istio-service-mesh-deepish-dive-architecture-traffic-control-security-and-observability
We’ll be diving a bit deeper, specifically into Istio's architecture, traffic management, security, and observability features.
[英文] Traffic Management
https://istio.io/latest/docs/concepts/traffic-management/
Istio’s traffic routing rules let you easily control the flow of traffic and API calls between services.
https://www.cloudnativedeepdive.com/managing-traffic-in-kubernetes-for-gateways-service-mesh/
There is always traffic moving throughout your cluster, whether it's north/south (ingress/egress) or east/west (service-to-service).
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.
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