蚂蚁金服Asys工程系统研发
校招全职蚂蚁集团2026届应届生招聘地点:北京 | 杭州状态:招聘
任职要求
1. 精通至少一门 Python/Go/C++ 等编程语言,并有良好的代码风格; 2. 了解分布式系统服务/并行计算系统设计与优化; 3. 熟悉主流深度学习框架及扩展库的使用及算子开发,例如TensorFlow/PyTorch/Megatron/Deepspeed/vLLM/Sglang等; 4. 好奇…
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工作职责
蚂蚁ASystem致力于打造下一代AI基础软件,并基于下一代的AI基础软件寻找通用智能的新方法,追求智能上限。 1. 负责训推一体框架的设计与开发,服务蚂蚁内部的强化学习场景; 2. 建设面向训推一体的显存管理体系和高性能数据存储方案; 3. 负责实时高性能训推系统设计与开发,如分布式训练加速策略、算子融合、编译优化、模型量化、混合精度、异构硬件加速等; 4. 负责整体性能优化与架构升级,持续提升训练/推理性能; 5. 与算法工程师深度合作,为重点项目进行算法与系统的联合优化。
包括英文材料
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.
Go+
https://www.youtube.com/watch?v=8uiZC0l4Ajw
学习Golang的完整教程!从开始到结束不到一个小时,包括如何在Go中构建API的完整演示。没有多余的内容,只有你需要知道的知识。
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
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
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
还有更多 •••
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