滴滴高级算法工程师-LLM(J241010010)
社招全职技术地点:北京状态:招聘
任职要求
1 人工智能、计算机、电子、数学等相关专业毕业,具备扎实的数据结构与算法基础,具备良好的数学思维能力。 2 熟悉有关Transfomer、BERT、GPT、MoE等方面的知识,对Llama,DeepSeek等大模型框架与其在业务应用、效率提升方面的实践有相关经历。 3 熟悉常用大模型Post-Training方法,包括PEFT、RLHF等相关技术 4 熟悉常用数据挖掘算法及其应用,掌握机器学习算法(如LR、GBDT、XGBoost、RL、DNN等),并具备实战经验。 5 编程基础扎实,熟悉至少一种深度学习框架(Pytorch,TensorFlow),并熟练掌握C++、Java、Python或Golang等语言之一。 6 具备优秀的算法设计和实现能力,能够独立完成算法等需求分析、方案设计、代码实现和效果评估。 7 热衷于了解业界前沿技术,洞悉人工智能国际会议的研究动态,具有强烈的钻研精神和主观能动性,能够适应快速变化的技术趋势。 其他优先条件: 有大模型背景和深度学习训练与应用经验者优先 在人工智能相关顶级会议发表过论文者优先 具备ACM/ICPC、CCPC、NOI等经历,编程能力优秀者优先 拥有大型系统架构设计与实践经验者优先 在Kaggle等比赛中取得优异成绩者优先 有英语浏览和书写能力者优先
工作职责
我们是滴滴网约车MPT部门的大模型研究开发团队,致力于以大模型为核心,打通数据、技术与业务链路,推动AI在智能运营与交易市场中的应用革新。我们的研究方向涵盖大模型驱动的数据挖掘、智能运营系统、以及核心交易机制的技术演进。 工作职责与方向包括: - 负责基于大模型的智能运营系统构建,包括但不限于利用Prompt、SFT、RLHF、Agent等技术,打造面向业务的单点工具建设和产品工具集成。 - 负责基于大模型的交易技术任务和基础技术方案研发,包括但不限于基于大模型的判别式任务构建、基于大模型的基础公共特征挖掘,和交易市场主栈问题(定价、分单)中LLM的应用方案探索。 - 密切关注行业的最新动态,跟踪研究最新技术和趋势,推进有价值的技术在公司内部落地,探索前沿的算法迭代,推动技术创新。 - 与工程团队紧密合作,推动模型的工程化部署,包括模型压缩、推理加速等环节。
包括英文材料
数据结构+
https://www.youtube.com/watch?v=8hly31xKli0
In this course you will learn about algorithms and data structures, two of the fundamental topics in computer science.
https://www.youtube.com/watch?v=B31LgI4Y4DQ
Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.
https://www.youtube.com/watch?v=CBYHwZcbD-s
Data Structures and Algorithms full course tutorial java
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/
BERT+
https://www.youtube.com/watch?v=xI0HHN5XKDo
Understand the BERT Transformer in and out.
GPT+
https://www.youtube.com/watch?v=kCc8FmEb1nY
We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3.
Llama+
https://github.com/LlamaFamily/Llama-Chinese
Llama中文社区,实时汇总最新Llama学习资料,构建最好的中文Llama大模型开源生态,完全开源可商用。
https://www.llama.com/docs/overview/
This guide provides information and resources to help you set up Llama including how to access the model, hosting, how-to and integration guides.
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
数据挖掘+
https://www.youtube.com/watch?v=-bSkREem8dM
Database vs Data Warehouse vs Data Lake
https://www.youtube.com/watch?v=7rs0i-9nOjo
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.
GBDT+
https://developers.google.com/machine-learning/decision-forests/intro-to-gbdt
Like bagging and boosting, gradient boosting is a methodology applied on top of another machine learning algorithm.
https://scikit-learn.org/stable/modules/ensemble.html
Ensemble methods combine the predictions of several base estimators built with a given learning algorithm in order to improve generalizability / robustness over a single estimator.
XGBoost+
[英文] What is XGBoost?
https://www.ibm.com/think/topics/xgboost
XGBoost (eXtreme Gradient Boosting) is a distributed, open-source machine learning library that uses gradient boosted decision trees, a supervised learning boosting algorithm that makes use of gradient descent.
https://www.youtube.com/watch?v=BJXt-WdeJJo
takes a deep dive into one of the most powerful machine learning algorithm, eXtreme Gradient Boosting, using a Jupyter notebook with Python.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
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.
Go+
https://www.youtube.com/watch?v=8uiZC0l4Ajw
学习Golang的完整教程!从开始到结束不到一个小时,包括如何在Go中构建API的完整演示。没有多余的内容,只有你需要知道的知识。
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.
Kaggle+
[英文] Kaggle Learn
https://www.kaggle.com/learn
Gain the skills you need to do independent data science projects.
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