高德地图高德-算法-专项
社招全职3年以上技术类-算法地点:北京状态:招聘
任职要求
我们期待的候选人 基础要求: 计算机、数学、AI相关专业硕士及以上学历,3年以上算法/工程经验(专家岗需5年以上)。 扎实的算法基础(如机器学习、深度学习、强化学习),精通Python/Java/Scala等开发语言。 熟悉分布式系统、大数据平台(如Hadoop/Spark/Flink)及工程化部署能力。 加分项: 在推荐系统、广告算法、多模态模型、强化学习等领域有落地经验。 发表过顶会论文或开源项目经验者优先。 我们提供 技术挑战:参与高德核心业务场景(如导航、搜索、广告)的算法创新与规模化应用。 成长资源:与顶尖团队合作,接触前沿AI技术,享有灵活的学术交流与晋升通道。 福利保障:具有竞争力的薪酬、弹性工作制、全面的福利体系。
工作职责
高德信息算法专项招聘方向 业务背景 高德地图作为行业领先的出行平台,持续探索AI与大数据技术在地图、导航、出行服务等领域的创新应用,现面向算法、工程、数据领域招聘顶尖人才,推动技术驱动业务增长与用户体验升级。 核心岗位方向 算法与AI应用 1. 推荐与个性化算法:负责用户兴趣建模、个性化推荐系统设计与优化(覆盖推荐算法专家、个性化推荐/搜索算法工程师)。 2. 广告算法:优化广告预估模型、创意策略、流量分配机制及增长路径(需熟悉CTR/CVR预估、机制设计)。 3. 强化学习与智能决策:研究强化学习在路径规划、动态资源分配等场景的落地应用。 4. 多模态内容理解:探索文本、图像、时空数据融合的多模态算法,提升内容分析与场景理解能力。 搜索与数据技术 1. 搜索算法:优化搜索排序、语义理解及RAG(检索增强生成)引擎开发(需熟悉NLP、信息检索技术)。 2. 用户画像与增长:构建用户行为分析体系,驱动商家/用户增长策略(需具备数据挖掘与增长分析经验)。
包括英文材料
学历+
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/
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.
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.
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.
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.
Scala+
分布式系统+
https://www.distributedsystemscourse.com/
The home page of a free online class in distributed systems.
https://www.youtube.com/watch?v=7VbL89mKK3M&list=PLOE1GTZ5ouRPbpTnrZ3Wqjamfwn_Q5Y9A
大数据+
https://www.youtube.com/watch?v=bAyrObl7TYE
https://www.youtube.com/watch?v=H4bf_uuMC-g
With all this talk of Big Data, we got Rebecca Tickle to explain just what makes data into Big Data.
Hadoop+
https://www.runoob.com/w3cnote/hadoop-tutorial.html
Hadoop 为庞大的计算机集群提供可靠的、可伸缩的应用层计算和存储支持,它允许使用简单的编程模型跨计算机群集分布式处理大型数据集,并且支持在单台计算机到几千台计算机之间进行扩展。
[英文] Hadoop Tutorial
https://www.tutorialspoint.com/hadoop/index.htm
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models.
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
推荐系统+
[英文] Recommender Systems
https://www.d2l.ai/chapter_recommender-systems/index.html
Recommender systems are widely employed in industry and are ubiquitous in our daily lives.
相关职位

社招8-10年算法专项团队
1、负责虎扑社区内容的业务算法,优化搜推全链路算法模块,持续迭代提升业务核心指标。 2、探索前沿领域NLP/大模型算法,针对业务需求提出合适的算法解决方案,推动方案在业务系统落地,包括搜索推荐、AIGC、智能对话等。 3、深度参与项目研发,与产品和业务团队同学保持密切配合,不断优化项目整体效益,提升用户体验。
更新于 2025-08-01
社招5年以上技术类-算法
1. 参与亿级用户规模的高德个性化搜索引导场景优化,应用机器学习/深度学习/大模型算法提升推荐结果指标 2. 负责多入口多场景下统一召回、粗排、精排算法优化;在多场景建模、用户行为序列建模、时空场景推荐等技术点上,应用业界领先的技术优化,取得指标收益。 3. 利用高德的庞大数据量,结合LBS时空数据的特点,通过海量数据/大模型分析挖掘用户潜在需求,指导推荐算法和策略的设计,提升推荐效果。
更新于 2025-08-07
社招3年以上技术类-算法
1.负责高德信息业务营销增长算法工作; 2.构建机器学习和运筹优化模型,基于数据与算法来解决营销领域的一系列问题,比如交易促成、商品定价、销量预测等; 3.通过数据洞察分析与挖掘,分析产品功能价值与优化点,发现潜在的营销增长机会; 4.和内部业务方紧密合作,发现和解决营销增长上的问题,并且基于大规模用户和产品数据用算法来解决业务问题。
更新于 2025-09-15