阿里巴巴超大规模大模型训练Infra构建和研发-阿里星
实习兼职阿里巴巴2027届实习生地点:北京状态:招聘
任职要求
1. 工程与算法基础:计算机相关专业背景,有极佳的工程实现能力,精通 C/C++ 与 Python;具备扎实的数据结构与算法功底,熟练掌握 GDB / Nsight 等调试与性能分析工具。 2. 大规模分布式经验:有大规模分布式系统开发和优化经验。对现代 GPU 集群通信机制及 NCCL 等通信库原理有深刻理解,有大模型分布式训练工程经验者优先。 3. 算法工程协同设计:对 LLM、多模态等大模型结构及其核心算法流程有…
登录查看完整任职要求
微信扫码,1秒登录
工作职责
1. 超大规模训练架构:负责百亿至万亿参数模型的分布式训练架构设计与演进。针对数千卡 GPU 互联场景,通过自顶向下的性能分析,利用 5D 并行以及通信优化策略,消除大规模分布式训练瓶颈,提升训练效率和线性加速比。 2. 极致性能优化与算子开发:深入软硬协同层,通过手写 CUDA / Triton 算子、算子融合及 XLA / MLIR 等编译优化技术,挖掘 GPU 硬件极致算力,打造一流的执行引擎,追求业界SOTA的 MFU。 3. 训练框架演进:结合前沿的大语言模型(LLM)与多模态模型结构,协同算法团队进行框架级优化(如 Checkpointing、显存优化、Overlap 通信掩盖),优化单位算力的模型效果。 4. AI 创新应用落地支撑:作为算力基座的核心支撑,支持行业顶尖的 GPT、AIGC、多模态模型在 AI 创新应用场景的业务落地,解决实际业务中的大规模与稳定性挑战,确保模型从训练到应用的顺畅衔接。
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/
C+
https://www.freecodecamp.org/chinese/news/the-c-beginners-handbook/
本手册遵循二八定律。你将在 20% 的时间内学习 80% 的 C 编程语言。
https://www.youtube.com/watch?v=87SH2Cn0s9A
https://www.youtube.com/watch?v=KJgsSFOSQv0
This course will give you a full introduction into all of the core concepts in the C programming language.
https://www.youtube.com/watch?v=PaPN51Mm5qQ
In this complete C programming course, Dr. Charles Severance (aka Dr. Chuck) will help you understand computer architecture and low-level programming with the help of the classic C Programming language book written by Brian Kernighan and Dennis Ritchie.
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
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.
数据结构+
https://www.youtube.com/watch?v=8hly31xKli0
In this course you will learn about algorithms and data structures, two of the fundamental topics in computer science.
https://www.youtube.com/watch?v=B31LgI4Y4DQ
Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.
https://www.youtube.com/watch?v=CBYHwZcbD-s
Data Structures and Algorithms full course tutorial java
GDB+
[英文] Debugging with GDB
https://betterexplained.com/articles/debugging-with-gdb/
A debugger lets you pause a program, examine and change variables, and step through code.
https://code.visualstudio.com/docs/cpp/cpp-debug
After you have set up the basics of your debugging environment as specified in the configuration tutorials for each target compiler/platform, you can learn more details about debugging C/C++ in this section.
https://opensource.com/article/21/3/debug-code-gdb
Troubleshoot your code with the GNU Debugger.
https://www.brendangregg.com/blog/2016-08-09/gdb-example-ncurses.html
gdb is the GNU Debugger, the standard debugger on Linux.
Nsight+
https://developer.nvidia.com/tools-tutorials
NVIDIA Nsight™ Developer tools are a suite of tools for building, profiling, and debugging accelerated applications.
https://www.youtube.com/watch?v=aQ1NYoRvp7o
Profile Python for AI and deep learning applications with NVIDIA's suite of Nsight Developer Tools.
https://www.youtube.com/watch?v=Iuy_RAvguBM
Join NVIDIA’s Jackson Marusarz for an introduction to NVIDIA Nsight Compute, a tool for in-depth analysis of CUDA kernel performance on GPUs.
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
还有更多 •••
相关职位
实习阿里巴巴研究型实
1.负责广告数据计算平台设计和开发,支持万亿级数据的交互式圈人、洞察、归因、报表场景。 2.负责广告定向数据产品研发,能提供架构设计和优化方案,并从技术上推进产品的快速迭代。 3.紧跟业界前沿,探索增强分析、智能营销助手等创新场景的技术解决方案。
更新于 2026-03-20北京
实习阿里巴巴2027
我们持续关注大模型后训练的多种场景,重点优化攻坚下面场景: 1、支持超长序列的模型的高效训练; 2、支持推理模型的高效训练,支持包括Agent RL、Search RL等多种有挑战的训练范式; 3、研发训推分离的RL框架,结合阿里云Cloud的基础设施来最大化提升训练的迭代速度。
更新于 2026-03-23北京|杭州|上海
实习阿里巴巴2027
我们持续关注大规模模型训练的性能和效率,我们重点关注下面几个方向: 1、通过专注的分布式训练框架的优化,持续提升超大规模语言模型的训练效率、性能和稳定性; 2、我们关注多种异构硬件设备,通过多种技术的优化来提升异构计算的性能; 3、通过算法系统一体的联合优化,在持续提升算法效果的前提下支持算法模型的快速迭代。
更新于 2026-03-23北京|杭州|上海