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Open nowPosted 94 days ago

音频表征算法工程师 - 音视频技术

ByteDance19,208 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now音频表征算法工程师 - 音视频技术ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 94 days ago

ByteDance median: 2 days open

The posting

团队介绍：视频与边缘部门承载了字节跳动的媒体内容分发基建及技术中台，支持了字节跳动全系产品，如抖音、今日头条、番茄小说、西瓜视频等APP的点播、直播、实时通信、图片等多媒体业务发展，同时将业务发展过程中沉淀下来的技术能力和工具，通过火山引擎对外输出，面向各行各业用户提供视频云产品和服务，愿景是为内外部业务伙伴提供最低成本、最优画质、最低延时、最安全可靠的富媒体内容分发解决方案，助力业务伙伴降本提效实现持续增长。

1、负责音频表征核心技术研发，聚焦语音、音乐和环境音等多场景音频的特征提取、表示学习与优化，构建高效、鲁棒的音频表征体系； 2、负责前沿技术调研与落地，跟踪深度学习、自监督学习和对比学习等领域在音频表征方向的最新进展（如Wav2Vec、HuBERT、AudioMAE等模型），并结合业务场景进行创新应用； 3、搭建音频表征模型的训练、评估与部署Pipeline，优化模型性能（精度、效率、泛化能力），满足量产级产品的工程化要求； 4、与算法工程、产品和业务等团队紧密协作，推动技术方案落地与迭代，输出技术文档与专利成果。

1、2027届获得硕士及以上学位，计算机科学、电子工程、信号处理、人工智能、声学等相关专业优先； 2、具备扎实的音频信号处理基础，深入理解傅里叶变换、梅尔频谱、MFCC、谱减法等传统音频特征提取方法，同时精通深度学习在音频领域的应用； 3、熟练掌握至少一种深度学习框架（PyTorch/TensorFlow），具备丰富的音频表征模型（自监督、半监督、有监督）设计、训练与调优经验； 4、具备良好的编程能力，熟练使用Python/C++，能够独立完成算法原型开发、实验验证与工程化适配； 5、具备较强的问题分析与解决能力，对技术有追求，具备良好的沟通协作与跨团队推动能力。

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