字节跳动资深音频音质算法专家-互娱研发
社招全职A246507地点:北京状态:招聘
任职要求
1、丰富的数字信号处理和人工智能/深度学习系统研发经验:智能音效/降噪/回声/去混响等音频前处理,声纹/唤醒,声音事件检测,语音识别,自然语言处理等一个或几个领域有项目实践; 2、熟悉数据结构和算法,深度网络模型设计和调优,熟练掌握Kaldi,TensorFlow,Pytorch等开源工具,有大规模训练数据集上进行模型训练和探索经验尤佳; 3、良好的团队合作意识和学习能力,有业务意识,对语音和音频领域技术有热情; 4、加分项: 1)在ACM/NOI/IOI/TopCoder获奖者优先; 2)有定点量化、指令集优化、深度模型优化等相关项目经验者优先; 3)有CPU,GPU,NPU,ARM,OpenCL,DSP等高性能计算优化经验者优先; 4)有相关音乐识别、音乐理解、对话助手经验的优先; 5)有相关音乐或NLP算法引擎开发经验的优先。
工作职责
1、负责公司音乐业务相关的音质音效开发与调优工作,相关研发技术在抖音、汽水音乐等产品中应用,满足音乐相关业务场景中用户不断增长的高阶听感的需求; 2、负责音乐产品(如流媒体平台、智能硬件、音乐制作工具等)的音频效果设计、调试与优化,包括EQ均衡、动态处理、空间混响等参数调整; 3、针对不同场景(如耳机/音箱播放、直播、车载环境)定制音效方案,确保听觉体验一致性与适应性; 4、与算法工程师合作,将音效参数转化为可落地的DSP(数字信号处理)代码或硬件调音方案; 5、研究用户听音习惯及行业趋势(如空间音频、AI生成音乐),提出创新音效功能设计(如自适应环境降噪、个性化声场调节); 6、通过A/B测试、用户反馈数据分析,持续迭代音效参数库与预设模板。
包括英文材料
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
语音识别+
https://www.youtube.com/watch?v=mYUyaKmvu6Y
Learn how to implement speech recognition in Python by building five projects.
https://www.youtube.com/watch?v=sR6_bZ6VkAg
How Rev.com harnesses human-in-the-loop and deep learning to build the world's best English speech recognition engine
NLP+
https://www.youtube.com/watch?v=fNxaJsNG3-s&list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S
Welcome to Zero to Hero for Natural Language Processing using TensorFlow!
https://www.youtube.com/watch?v=R-AG4-qZs1A&list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Natural Language Processing tutorial for beginners series in Python.
https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4
The foundations of the effective modern methods for deep learning applied to NLP.
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/
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.
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.
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