小红书大模型推理引擎研发工程师（实习）
实习兼职引擎地点：北京状态：招聘
任职要求
1、优秀的代码能力、数据结构和基础算法功底，熟悉C++/Python开发，熟悉 Linux/Git 开发环境； 2、熟悉至少一种主流基础深度学习训练或推理框架（TensorFlow/PyTorch/PaddlePaddle/TensorRT等）的使用和实现； 3、熟悉主流LLM模型结构，熟悉至少一种主流LLM推理框架（vLLM/SGLang/TensorRT-LLM等）的使用和实现； 4、熟悉GPU硬件架构，了解GPU 软件栈（CUDA，cuDNN)，具备 GPU 性能分析的能力； 5、有强烈的工作责任心，较好的学习能力、沟通协作能力和自驱力，能和团队一起探索新技术，推进技术进步。 加分项： 1、熟悉CUDA编程，有TensorRT或其它AI加速库、高性能算子开发经验者优先； 2、熟悉至少一种AI编译加速组件者优先，包含但不限与TorchInductor/TVM/Triton/XLA等； 3、了解并行计算、网络通信、系统优化和集群硬件架构等相关知识者优先； 4、熟悉NCCL/RDMA/IB/RoCE相关知识者优先； 5、有优秀开源项目经历者优先。
工作职责
1、参与/负责研发面向大语言模型(LLM)/多模态大模型(MLLM)等类型模型的推理服务框架； 2、通过并行计算优化、分布式架构优化、异构调度等多种框架技术，打造高效、易用、领先的AI推理框架； 2、深度参与周边深度学习系统多个子方向的工作，包括但不限于模型管理、推理部署、日志/监控、工作流编排等； 3、与全公司各业务算法部门深度合作，为重点项目进行算法与系统的联合优化，支撑业务目标达成。
包括英文材料
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
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.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.
Linux+
https://ryanstutorials.net/linuxtutorial/
Ok, so you want to learn how to use the Bash command line interface (terminal) on Unix/Linux.
https://ubuntu.com/tutorials/command-line-for-beginners
The Linux command line is a text interface to your computer.
https://www.youtube.com/watch?v=6WatcfENsOU
In this Linux crash course, you will learn the fundamental skills and tools you need to become a proficient Linux system administrator.
https://www.youtube.com/watch?v=v392lEyM29A
Never fear the command line again, make it fear you.
https://www.youtube.com/watch?v=ZtqBQ68cfJc
Git+
https://www.youtube.com/watch?v=rH3zE7VlIMs
Learn Git from start to finished in this full course written by ThePrimeagen.
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.
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.
PaddlePaddle+
https://learnopencv.com/paddlepaddle/
PaddlePaddle (PArallel Distributed Deep LEarning) is an open-source deep learning framework released by Baidu in 2016.
https://www.paddlepaddle.org.cn/tutorials
本课程采用飞桨特色的「横纵式」 教学法，从易到难，学习难度逐层递进，并结合图形和案例进行讲解，力求让刚接触深度学习的读者可以快速理解。
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.
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
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
CUDA+
https://developer.nvidia.com/blog/even-easier-introduction-cuda/
This post is a super simple introduction to CUDA, the popular parallel computing platform and programming model from NVIDIA.
https://www.youtube.com/watch?v=86FAWCzIe_4
Lean how to program with Nvidia CUDA and leverage GPUs for high-performance computing and deep learning.
相关职位
实习核心本地商业-基
1.围绕大模型异构训练集群，尤其是非NV GPU大规模异构硬件集群，面向大模型预训练、Finetune等场景进行新模型使能，系统分析/优化，业务支撑等工作，包括分布式优化框架，AI框架，网络集合通信，算子等方面内容； 2.负责大模型推理引擎的研发和优化，包括推理系统优化、模型量化压缩和模型部署； 3. 熟悉NLP类模型训练场景，有GPT，LlaMa、DeepSeek等相关知识和经验者优先 4. 熟悉视觉类，多模态大模型训练场景，有ViT， Swin Transformer, Stable Diffusion, MoE相关知识和经验者优先 5. 熟悉Megatron, Deepspeed, Colossal AI, FSDP等分布式框架，有相关知识、使用和调优经验者优先 6. 熟悉以下推理框架者优先，如FasterTransformer、vllm、sglang、LMDeploy、TensorRT-LLM等； 7. 熟悉PyTorch分布式场景，有二次开发经验，系统调优知识和经验者优先 8. 熟悉集合通信原理和基本知识，对NCCL有大规模使用，调优经验者优先 9. 熟悉算子开发流程，有CUDA编程知识和相关经验者优先 10. 熟悉NV GPU架构，对其他类型AI芯片有使用经验者优先
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