地平线AI 软件系统架构师
社招全职软件序列地点：上海 | 深圳状态：招聘
任职要求
1、精通计算机体系结构，熟悉ARM/x86/GPU/NPU架构及指令集优化 2、深入理解AI软件栈：编译器（LLVM/MLIR）、推理框架（TFLite/ONNX Runtime）、驱动开发（Linux Kernel/Driver） 3、熟悉主流AI模型（CNN/Transformer）及优化技术（量化、剪枝、知识蒸馏） 4、有芯片底层开发经验者优先（如SIMD编程、DSP开发、Cache一致性设计） 5、熟练使用C++/Python，具备高性能代码优化经验（如NEON/OpenCL/CUDA） 6、熟悉AI部署工具链（如TVM、TensorRT、AITemplate） 7、具备产品思维，能从业务需求反推技术架构设计 8、强跨团队推动能力，能主导技术决策并落地
工作职责
1、全栈AI系统架构设计 -主导AI软件栈（编译工具链、Runtime、编程模型、驱动）与硬件（ARM/GPU/NPU等）的协同设计，优化模型推理性能与能效。 -在芯片或产品架构定义阶段，将软件需求前置化，提出硬件可编程性、指令集扩展等关键设计建议。 2、技术规划与方案落地 -制定AI技术中长期路线图，评估新兴技术（如稀疏计算、量化编译、异构加速）在业务场景中的可行性。 -推动跨团队（算法、芯片、OS）协作，解决从模型到硬件的部署瓶颈（如算子适配、内存优化）。 3、算法-硬件协同优化 -结合模型结构（如Transformer/CNN）和目标硬件特性（ARM多核/向量指令集），设计定制化加速方案。 -参与前沿算法研究（如轻量化模型设计），确保其与底层硬件的高效匹配。 4、性能调优与工具链开发 -主导AI编译器（如MLIR、TVM）或Runtime的深度优化，提升跨平台部署效率。 -开发性能分析工具，定位系统级瓶颈（如DDR带宽、Cache命中率）。 。
包括英文材料
LLVM+
https://llvm.org/docs/GettingStarted.html
Welcome to the LLVM project!
https://llvm.org/docs/tutorial/
This is the “Kaleidoscope” Language tutorial, showing how to implement a simple language using LLVM components in C++.
https://mcyoung.xyz/2023/08/01/llvm-ir/
“LLVM” is an umbrella name for a number of software components that can be used to build compilers.
https://www.youtube.com/watch?v=Lvc8qx8ukOI
This is the first lecture from the "Programming Language with LLVM" course where we build a full programming language similar to JavaScript from scratch, using LLVM compiler infrastructure.
ONNX+
https://github.com/onnx/tutorials
Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models.
[英文] Introduction to ONNX
https://onnx.ai/onnx/intro/
This documentation describes the ONNX concepts (Open Neural Network Exchange).
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
内核+
https://www.youtube.com/watch?v=C43VxGZ_ugU
I rummage around the Linux kernel source and try to understand what makes computers do what they do.
https://www.youtube.com/watch?v=HNIg3TXfdX8&list=PLrGN1Qi7t67V-9uXzj4VSQCffntfvn42v
Learn how to develop your very own kernel from scratch in this programming series!
https://www.youtube.com/watch?v=JDfo2Lc7iLU
Denshi goes over a simple explanation of what computer kernels are and how they work, alonside what makes the Linux kernel any special.
CNN+
https://learnopencv.com/understanding-convolutional-neural-networks-cnn/
Convolutional Neural Network (CNN) forms the basis of computer vision and image processing.
[英文] CNN Explainer
https://poloclub.github.io/cnn-explainer/
Learn Convolutional Neural Network (CNN) in your browser!
https://www.deeplearningbook.org/contents/convnets.html
Convolutional networks(LeCun, 1989), also known as convolutional neuralnetworks, or CNNs, are a specialized kind of neural network for processing data.
https://www.youtube.com/watch?v=2xqkSUhmmXU
MIT Introduction to Deep Learning 6.S191: Lecture 3 Convolutional Neural Networks for Computer Vision
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
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
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.
OpenCL+
https://developer.nvidia.com/opencl
OpenCL™ (Open Computing Language) is a low-level API for heterogeneous computing that runs on CUDA-powered GPUs.
https://engineering.purdue.edu/~smidkiff/ece563/NVidiaGPUTeachingToolkit/Mod20OpenCL/3rd-Edition-AppendixA-intro-to-OpenCL.pdf
we will give a brief overview of OpenCL for CUDA programers.
[英文] Hands On OpenCL
https://handsonopencl.github.io/
An open source two-day lecture course for teaching and learning OpenCL
https://leonardoaraujosantos.gitbook.io/opencl/chapter1
Open Computing Language is a framework for writing programs that execute across heterogeneous platforms.
https://ulhpc-tutorials.readthedocs.io/en/latest/gpu/opencl/
OpenCL came as a standard for heterogeneous programming that enables a code to run in different platforms.
https://www.youtube.com/watch?v=4q9fPOI-x80
This presentation will show how to make use of the GPU from Java using OpenCL.
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.
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.
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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