字节跳动NLP算法Leader-抖音
社招全职5年以上A209885地点:北京状态:招聘
任职要求
1、对NLP技术有深刻的技术理解,长期跟进相关技术的学术研究和行业应用,包括但不限于: (1)推荐、搜索、广告等大规模机器学习行业经验; (2)机器学习/CV/音频/NLP等行业经验; (3)机器学习/CV/音频/人工智能相关领域会议论文; 2、5年以上的从业经历,对NLP相关业务有深入的理解,在类似业务有算法团队经历者优先; 3、优秀的分析问题和解决问题的能力,对解决具有挑战性问题充满激情,能够将机器学习算法和业务结合解决现实问题; 4、具备算法团队的管理能力,能够紧跟当前的技术趋势,设计整个团队的技术架构,规划中长期发展路线。
工作职责
1、负责内容理解和内容安全算法方向的NLP技术团队,为不同业务和算法方向的团队提供NLP技术支持; 2、建设文本、多模态领域的基础技术能力,包括但不限于: (1)为多样的业务线、问题域提供LLM基座模型pretrain,降低大团队成本并提升下游模型应用的效果; (2)建设通用的技术能力,如数据工程、RAG、基础工程架构等; (3)为创新业务提供基础技术能力; 3、长期投入NLP算法方向的探索研究,做到在NLP技术上的跟进和创新。
包括英文材料
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.
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.
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/
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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