携程搜索引擎开发工程师(MJ029378)
社招全职住宿业务开发地点:上海状态:招聘
任职要求
1. 计算机相关专业本科及以上学历,扎实的算法和编程能力。 2. 拥有搜索引擎、信息检索、机器学习等相关从业经验。 3. 具有海量数据处理和分布式计算开发经验者优先。 4. 责任心强 积极主动 勇于接受挑战 具有创新精神 对移动搜索产品有热情。 5. 熟练掌握Java,熟悉elasticsearch、Lucene框架。 6. 具有良好的沟通能力和良好的团队合作精神。
工作职责
1. 参与携程酒店核心搜索业务的架构设计优化及功能开发,如全文检索引擎、数据引擎,保障系统的高可用、高吞吐、低延迟。 2. 参与携程酒店搜索平台系统的架构设计和开发,为业务提供灵活、稳定、高效的解决方案。 3. 跟进项目进度,接口规范制定,技术文档编写,确保项目进度和质量。针对搜索的业务现状,探索和创新搜索技术。
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/
信息检索+
https://nlp.stanford.edu/IR-book/information-retrieval-book.html
Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.
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.
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.
ElasticSearch+
https://www.youtube.com/watch?v=a4HBKEda_F8
Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations.
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