百度大模型算法工程师(J93514)
社招全职ACG地点:北京状态:招聘
任职要求
-拥有扎实的计算机基础,计算机或相关专业本科及以上学历 -掌握NLP基本算法,理解并掌握大模型的预训练、SFT、RLHF -有基于LLM的实际项目经验,如构建对话机器人、智能问答、智能问数、AI助手、RAG系统等 -熟悉并掌握至少一种主流深度学习框架(Paddle,Pytorch,Tensorflow,Mxnet,Caffe等) -对Function Calling、Tool Use、Multi-Agent等原理和实践框架有深入理解者优先 -具有良好的逻辑思维能力、表达及分析问题能力,具备优秀的团队协作精神 -在机器学习/NLP领域学术会议发表过高水平文章者优先
工作职责
-参与Multi-Agent框架的设计与实现,包括意图识别、任务规划、记忆机制以及Code Agent等核心模块建设 -参与多模态检索的召回与排序优化,不断提升跨模态检索的准确性与用户体验 -参与文档解析、语义理解与信息抽取等方向的研究与工程落地,推动端到端效果持续优化 -持续探索跟进学术与业界前沿进展并进行落地
包括英文材料
学历+
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.
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/
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
SFT+
https://cameronrwolfe.substack.com/p/understanding-and-using-supervised
Understanding how SFT works from the idea to a working implementation...
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
PaddlePaddle+
https://learnopencv.com/paddlepaddle/
PaddlePaddle (PArallel Distributed Deep LEarning) is an open-source deep learning framework released by Baidu in 2016.
https://www.paddlepaddle.org.cn/tutorials
本课程采用飞桨特色的「横纵式」 教学法,从易到难,学习难度逐层递进,并结合图形和案例进行讲解,力求让刚接触深度学习的读者可以快速理解。
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.
MXNet+
https://www.tutorialspoint.com/apache_mxnet/index.htm
Apache MXNet is a powerful deep learning framework that supports both symbolic and imperative programming.
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
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.
相关职位
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-负责产品平台、服务端、算法等相关测试工作(包括传统AI模型/大模型) -负责需求分析、测试用例设计、包括但不限于功能、性能 效果及高可用等测试维度的支持 -负责CI/CD 建设,协助提升研发效能并对产品及流程持续性提出改进建议 -负责大模型相关产品、算法等测试
更新于 2025-09-17
社招1年以上算法开发岗
1、参与生成式大模型能力构建;不局限于模型设计、prompt优化、预训练、模型推理加速、其他能力建设等; 2、采用最先进的并行处理和分布式学习技术,制定并执行性能优化策略,显著提升大型语言模型的训练速度和推理能力,例如跟进DeepSeek R1技术架构等,确保技术行业领先; 3、推进大模型技术在京东物流各个业务场景落地,包括不限于智能问答、智能数据分析、智能决策以及Computer Use等,助力业务流程优化,增质提效; 4、深度探索大语言模型方向,保持技术领先优势,推动京东物流在行业内树立高效、精准的大模型/多模态大模型应用标杆,并取得业务收益。
更新于 2025-06-09