影石AI开发工程师
社招全职3年以上地点:深圳状态:招聘
任职要求
1、精通c++开发,并且有3年及以上的c++开发经验,熟悉软件设计模式; 2、掌握操作系统原理、掌握并发计算,有比较丰富的多线程开发经验; 3、具备机器学习、深度学习基础知识,了解以上算法基本输入、输出与工作过程; 4、熟悉AI推理框架,有tensorrt,openvino,onnx,mnn,coreml等一种或者多种推理框架开发的优先; 5、熟练使用性能分析工具,有intel-vtune-profile/perf/nsight-system等一种或者多种性能分析工具的优先。
工作职责
1. 使用C++实现AI算法的工程化,根据业务特性进行软件架构评估、设计和开发; 2. 协同AI算法工程师完成模型转换、自定义算子支持、模型量化、推理效果对齐等工作; 3. 开发及维护C++AI算法库,输出sdk,跟进或推进各端进行接入及效果和性能对齐。
包括英文材料
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
多线程+
https://liaoxuefeng.com/books/java/threading/basic/index.html
和单线程相比,多线程编程的特点在于:多线程经常需要读写共享数据,并且需要同步。
https://www.youtube.com/watch?v=_uQgGS_VIXM&list=PLsc-VaxfZl4do3Etp_xQ0aQBoC-x5BIgJ
https://www.youtube.com/watch?v=IEEhzQoKtQU
https://www.youtube.com/watch?v=mTGdtC9f4EU&list=PLL8woMHwr36EDxjUoCzboZjedsnhLP1j4
https://www.youtube.com/watch?v=TPVH_coGAQs&list=PLk6CEY9XxSIAeK-EAh3hB4fgNvYkYmghp
https://www.youtube.com/watch?v=xPqnoB2hjjA
This video is an introduction to multithreading in modern C++.
https://www.youtube.com/watch?v=YKBwKy5PrpQ
Rust threading is easy to implement and improves the efficiency of your applications on multi-core systems!
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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/
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.
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).
MNN+
https://github.com/alibaba/MNN?tab=readme-ov-file#intro
MNN is a highly efficient and lightweight deep learning framework.
Core ML+
[英文] Getting Started
https://apple.github.io/coremltools/docs-guides/source/introductory-quickstart.html
Core ML Tools can convert trained models from other frameworks into an in-memory representation of the Core ML model.
https://developer.apple.com/machine-learning/core-ml/
Core ML is optimized for on-device performance of a broad variety of model types by leveraging Apple silicon and minimizing memory footprint and power consumption.
https://www.youtube.com/watch?v=g3yj9_DHrME
Bring the power of machine learning directly to your apps with Core ML.
Perf+
https://perfwiki.github.io/main/
perf is powerful: it can instrument CPU performance counters, tracepoints, kprobes, and uprobes (dynamic tracing).
https://www.brendangregg.com/bpf-performance-tools-book.html
This book can help you get the most out of your systems and applications, helping you improve performance, reduce costs, and solve software issues.
[英文] perf Examples
https://www.brendangregg.com/perf.html
These are some examples of using the perf Linux profiler, which has also been called Performance Counters for Linux (PCL), Linux perf events (LPE), or perf_events.
https://www.youtube.com/watch?v=M6ldFtwWup0
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.
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