奇虎36026秋-AIGC算法工程师-算法研究（北京）-4908(J11807)
校招全职算法类地点：北京状态：招聘
任职要求
1、硕士及以上学历，计算机科学、软件工程、人工智能等相关专业 2、扎实掌握机器学习/深度学习基础理论，熟悉CNN、RNN、Transformer等主流模型原理 3、熟练掌握Python编程语言，具备良好的算法实现与代码优化能力 4、熟悉PyTorch/TensorFlow等深度学习框架，有模型训练与调优经验者优先 5、了解多智能体系统、强化学习或自然语言处理相关技术，有相关项目经验者优先 6、具备较强的逻辑思维能力和问题解决能力，能够独立完成算法设计与实现
工作职责
该岗位专注于算法研发与优化，涉及React引擎框架、多智能体调度算法及上下文工程等核心技术领域，要求候选人具备扎实的算法理论基础和工程实践能力，能够通过技术创新优化业务流程与引擎性能，推动AI技术在实际场景中的落地应用。 1、参与React引擎框架的设计与开发，优化前端算法性能及用户交互体验 2、负责多智能体调度算法的研究与实现，解决复杂场景下的协同决策问题 3、开展上下文工程相关技术研究，提升模型对多轮交互场景的理解与响应能力 4、分析业务需求并转化为技术方案，推动算法从原型验证到产品化落地的全流程 5、优化现有算法流程与引擎架构，提升系统稳定性、可扩展性及运行效率 6、跟踪业界前沿技术动态（如强化学习、分布式训练等），探索在业务场景中的创新应用 7、与产品、研发团队协作，参与AI项目的需求分析、技术评审及交付验收
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.
CNN+
https://learnopencv.com/understanding-convolutional-neural-networks-cnn/
Convolutional Neural Network (CNN) forms the basis of computer vision and image processing.
[英文] CNN Explainer
https://poloclub.github.io/cnn-explainer/
Learn Convolutional Neural Network (CNN) in your browser!
https://www.deeplearningbook.org/contents/convnets.html
Convolutional networks(LeCun, 1989), also known as convolutional neuralnetworks, or CNNs, are a specialized kind of neural network for processing data.
https://www.youtube.com/watch?v=2xqkSUhmmXU
MIT Introduction to Deep Learning 6.S191: Lecture 3 Convolutional Neural Networks for Computer Vision
RNN+
https://d2l.ai/chapter_recurrent-neural-networks/rnn.html
A neural network that uses recurrent computation for hidden states is called a recurrent neural network (RNN).
https://www.deeplearningbook.org/contents/rnn.html
Recurrent neural networks, or RNNs (Rumelhart et al., 1986a), are a family of neural networks for processing sequential data.
https://www.ibm.com/think/topics/recurrent-neural-networks
A recurrent neural network or RNN is a deep neural network trained on sequential or time series data to create a machine learning (ML) model that can make sequential predictions or conclusions based on sequential inputs.
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文，免费，零起点，完整示例，基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
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/
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.
智能体+
https://learn.microsoft.com/en-us/shows/ai-agents-for-beginners/
In this 10-lesson course we take you from concept to code while covering the fundamentals of building AI agents.
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
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.
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.
相关职位
校招算法类
主要负责大模型评测体系构建、性能分析及优化工作，要求候选人具备Agent深度定制开发能力，掌握提示词微调和模型部署推理加速技术，致力于提升大模型在实际业务场景中的性能表现。 1. 算法研究与优化 - 研究和跟踪人工智能领域的前沿技术发展，包括但不限于大语言模型、计算机视觉、多模态融合等方向 - 针对业务场景优化现有AI算法，提升模型性能、效率和部署可行性 - 参与创新算法原型的构建和验证实验 2. 应用场景落地 - 深入理解业务需求，将AI技术与实际应用场景结合 - 设计并实现算法到产品的转化路径，解决落地过程中的技术挑战 - 优化模型在真实环境中的性能表现，包括精度、速度、资源占用等方面 3. 效果评估与迭代 - 设计科学的评估方法，量化算法性能和业务价值 - 收集用户反馈和业务数据，持续迭代优化算法 - 撰写技术文档和研究报告，分享研究成果和应用经验
更新于 2025-09-02
校招算法类
1. 面向业务场景：互联网图文内容业务、视频内容业务及集团AI创新业务 2. 结合业务需求，在可控图像生成方向、可控图像编辑方向、可控视频编辑方向进行前沿工作的跟踪、研究及落地，并对业务进行技术引领和落地支撑
更新于 2025-09-02
校招算法类
1. 面向业务场景：互联网图文搜索、推荐、广告业务，AIoT智能硬件业务，数智化toB业务 2. 结合业务需求，在图文内容理解、跨模态图文对齐、多模态大模型、开放世界目标检测等方向进行前沿工作的跟踪、研究及落地，并对业务进行技术引领和落地支撑
更新于 2025-09-02
校招算法类
1、探索AIGC领域相关算法研究和应用落地 2、根据公司业务，根据特定场景进行算法分析和优化，面向场景包括但不限于文档智能、规划、创意文案/报告生成等 3、精通自然语言处理算法，对计算机视觉/语音语义/推荐等相关模型有了解，并对多模态算法持续follow和研究
更新于 2025-09-02