字节跳动内容安全视频理解算法工程师—抖音
社招全职SHTP地点:北京状态:招聘
任职要求
1、具有扎实的机器学习基础,推荐系统、计算机视觉、图像处理、模式识别、语音识别、机器学习、自然语言处理等相关专业,数理功底扎实,自学能力强; 2、熟悉TensorFlow/MxNet/Caffe等框架,熟练使用C++/Python编程; 3、有计算机视觉、NLP等相关…
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工作职责
1、负责抖音/抖音火山版等产品内容安全相关的视频理解相关AI算法的研究开发; 2、从事AI深度学习(视频理解,自然语言处理,语音等领域)前沿技术的探索与研发; 3、从事短视频/直播等相关业务的内容分析,包括但不限于视频分类、场景识别、目标检测与跟踪、图像分类、音频分类和特征提取、聚类、OCR、文本模型等技术,并应用于实际业务产品中。
包括英文材料
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.
推荐系统+
[英文] Recommender Systems
https://www.d2l.ai/chapter_recommender-systems/index.html
Recommender systems are widely employed in industry and are ubiquitous in our daily lives.
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
图像处理+
https://opencv.org/blog/computer-vision-and-image-processing/
This fascinating journey involves two key fields: Computer Vision and Image Processing.
https://www.geeksforgeeks.org/python/image-processing-in-python/
Image processing involves analyzing and modifying digital images using computer algorithms.
https://www.youtube.com/watch?v=kSqxn6zGE0c
In this Introduction to Image Processing with Python, kaggle grandmaster Rob Mulla shows how to work with image data in python!
模式识别+
https://www.mathworks.com/discovery/pattern-recognition.html
Pattern recognition is the process of classifying input data into objects, classes, or categories using computer algorithms based on key features or regularities.
https://www.microsoft.com/en-us/research/wp-content/uploads/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science.
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.
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.
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相关职位
社招JQWKP
1、负责抖音/抖音火山版等产品内容安全相关的视频理解相关AI算法的研究开发; 2、从事AI深度学习(视频理解,自然语言处理,语音等领域)前沿技术的探索与研发; 3、从事短视频/直播等相关业务的内容分析,包括但不限于视频分类、场景识别、目标检测与跟踪、图像分类、音频分类和特征提取、聚类、OCR、文本模型等技术,并应用于实际业务产品中。
更新于 2021-04-06深圳
社招J9PEP
1、负责抖音/抖音火山版等产品内容安全相关的视频理解相关AI算法的研究开发; 2、从事AI深度学习(视频理解,自然语言处理,语音等领域)前沿技术的探索与研发; 3、从事短视频/直播等相关业务的内容分析,包括但不限于视频分类、场景识别、目标检测与跟踪、图像分类、音频分类和特征提取、聚类、OCR、文本模型等技术,并应用于实际业务产品中。
更新于 2021-07-14上海
校招A73145A
团队介绍:国际化内容安全平台团队致力于为字节跳动国际化产品的用户维护安全可信赖环境,通过开发、迭代机器学习模型和信息系统以更早、更快发掘风险、监控风险、响应紧急事件,以人工智能技术支持业务发展,力求更高效、更敏捷、更全能地维护站内生态安全。 1、参与多模态大模型(LLM/VLM)的研发工作,探索视频理解与内容安全任务中的前沿技术; 2、协助进行大模型预训练、指令微调(SFT)和主动学习(RLHF),提升模型在国际化短视频安全数据集上表现; 3、参与标注与评测体系的建设,支持高质量数据集的构建与模型效果验证; 4、与团队成员合作,推动算法在实际审核场景中的落地与性能优化。
更新于 2025-08-25上海