字节跳动面向国际电商场景的大模型应用-国际电商(新加坡)LLM Applications for International E-commerce Scenarios-Global E-Commerce (Singapore)
校招全职A256165A地点:新加坡状态:招聘
工作描述
任职要求 1、2027届毕业,获得博士学位,计算机科学、人工智能、数学或相关专业; 2、人工智能/机器学习专业能力:对深度学习、自然语言处理、计算机视觉、强化学习、生成式模型或多模态学习领域有深入理解及相关研究经验; 3、编程与工程能力:熟练掌握主流编程语言及机器学习框架(如PyTorch、TensorFlow),同时具备出色的问题解决能力、自主学习能力与团队协作能力。 加分项 1、学术能力:在国际人工智能/计算机领域顶级会议或期刊(如NeurIPS、ICML、ICLR、CVPR、ACL、KDD、SIGIR、WWW)发表过论文,或在权威算法竞赛中取得优异名次; 2、领域实践成果:主导或参与过搜索、广告、推荐系统或大语言模型(LLMs)相关核心项目,具备实操经验; 3、高级多模态应用能力:在多模态大模型领域具备专项技术专长,尤其擅长长文本处理,或拥有影视剧集领域相关应用落地经验。 1.Education & Foundation: Ph.D. in Computer Science, AI, Mathematics, or a related field, with a strong foundation in data structures, algorithms, and mathematical modeling; 2.AI/ML Expertise: Solid understanding and research experience in Deep Learning, NLP, CV, Reinforcement Learning, Generative Models, or Multimodal Learning; 3.Coding & Engineering: Proficient in major programming languages and machine learning frameworks (e.g., PyTorch, TensorFlow), combined with excellent problem-solving, self-learning, and teamwork skills. Preferred Qualifications 1.Academic Excellence: Proven track record of publications in international AI/CS conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, KDD, SIGIR, WWW) or top rankings in recognized algorithmic competitions; 2.Domain-Specific Impact: Hands-on experience in leading or participating in key projects related to Search, Advertising, Recommendation systems, or Large Language Models (LLMs); 3.Advanced Multimodal Applications: Specialized expertise in multimodal large models, particularly in …
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包括英文材料
学历+
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.
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.
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.
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
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.
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.
NeurIPS+
https://neurips.cc/
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