阿里巴巴研究型实习生-面向全场景智能的大模型效能优化与智能体演进研究
实习兼职阿里巴巴研究型实习生地点:杭州状态:招聘
工作描述
任职要求 1、计算机科学、人工智能、电子工程等相关专业在读博士; 2、有 AI 算法/系统、高性能计算方向的顶会/顶刊论文发表; 3、扎实的 C/C++ 和 Python 编程能力,具备良好的代码工程素养; 4、熟悉 PyTorch,有实际模型训练或推理的项目经验; 5、每周至少实习 4 天,持续 3 个月以上。 加分项(满足任一即可) 1、有自动驾驶/图像/视频生成/推荐等领域相关项目经验者优先; 2、熟悉训练推理优化工具链(DeepSpeed / Megatron / TensorRT / ONNX Runtime / torch.compile),有实际加速经验; 3、有模型量化实践经验(GPTQ / AWQ / SmoothQuant / FP8 等),了解量化对生成质量的影响评估; 4、有推理引擎开发或大规模在线推理服务经验; 5、有 CUDA / Triton 算子开发经验,理解 GPU 架构(SM、Warp、共享内存、指令流水线等)。 工作职责 我们正在寻找对大模型在各种场景智能下的效能优化…
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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/
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.
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.
自动驾驶+
https://www.youtube.com/watch?v=_q4WUxgwDeg&list=PL05umP7R6ij321zzKXK6XCQXAaaYjQbzr
Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen)
https://www.youtube.com/watch?v=NkI9ia2cLhc&list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
DeepSpeed+
https://www.youtube.com/watch?v=pDGI668pNg0
Megatron+
https://www.youtube.com/watch?v=hc0u4avAkuM
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.
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