AI Intern - KG

This position is not available in GPP database. Talent Acquisition team member will fill in the Posting description after intake meeting.

Qualifications

Job title: AI Intern - KG

Job Summary:

-Exploring the application scenarios of knowledge graph in the fields of automotive and intelligent diagnosis

• Design and develop graph database
• Build and optimize the application system based on graph database
• Evaluate and test the application technology related to the graph data
• Maintain the graph database

• Develop and test the graph database, including the structuring of the data, and the data storage and updating of the graph database.
• Participate in the design of graph database system based on business scenarios, including node/edge design, attribute definition, Schema building, etc.
• Write efficient graph query statements (Cypher/Gremlin).
• Design and implement graph database related service interfaces to support the interface and integration of graphs with upstream and downstream systems.
• Assist in the development of natural language entity extraction, relationship extraction, etc. to support the construction of knowledge graphs.
• Participate in the deployment, monitoring and operation and maintenance of the graph database platform to ensure the stable operation of the graph system in the production environment.
• Write technical documents and reports: Write documents and reports on the development, testing and application of knowledge graph, and record the work results and lessons learned.
• Present compelling and validated stories to team members and stakeholders throughout and after the internship.
• Assist in the development of graph database visualization and display functions to achieve interactive browsing and analysis of structured graphs. Explore and apply advanced algorithmic techniques for graph databases such as Neo4j, AWS Neptune. Track and test new function of graph database or open source graph tools.

• Undergraduate or graduate student in Computer Science/Data Science/Artificial Intelligence or related disciplines: Solid knowledge of computer science fundamentals and familiarity with data structures, algorithms, programming languages, etc.
• Familiarity with at least one graph database system (e.g. Neo4j, AWS Neptune) and proficiency with a graph database language (e.g. Cypher or Gremlin, etc.).
• Familiarity with Python or other programming languages: Proficiency in writing and developing code in Python or other programming languages.
• Relevant knowledge graph project experience: Participated in NLP / KG related project development, such as chatbot, intelligent Q&A system, etc.
• Familiarity with NLP related technical solutions (e.g. entity recognition, relationship extraction, etc.) is a plus.
• Familiarity with Linux operating system is a plus.
• Good learning and problem solving skills: Ability to learn new knowledge and technologies quickly and solve problems independently.
• Good communication and teamwork skills: able to communicate effectively with team members and collaborate to complete project tasks.

• 探索知识图谱在汽车和智能诊断领域的应用场景
• 设计和开发图数据库
• 构建和优化基于图数据库的应用系统
• 评估和测试图数据相关应用技术
• 维护图数据库

• 图数据库的开发与测试，包括数据的结构化、图数据库的数据存储和更新等。
• 基于业务场景参与图数据库系统的设计，包括节点/边设计、属性定义、Schema 建立等。
• 编写高效的图查询语句（Cypher/Gremlin）。
• 设计并实现图数据库相关的服务接口，支持图谱与上下游系统的对接与集成。
• 协助进行自然语言的实体抽取、关系抽取等开发，以支持知识图谱的构建。
• 参与图数据库平台的部署、监控和运维，保障图系统在生产环境下的稳定运行。
• 撰写技术文档和报告: 撰写关于知识图谱在开发、测试和应用的文档和报告，记录工作成果和经验教训。
• 在整个实习期间和实习结束后，向团队成员和利益相关者展示令人信服的、经过验证的故事。
• 协助开发图数据库可视化展示功能，实现结构化图谱的交互式浏览与分析。探索并应用Neo4j、AWS Neptune等图数据库的高级算法技术。跟踪并测试图数据库的新功能或开源图谱工具。

• 计算机科学/数据科学/人工智能或相关专业的在读本科或研究生: 具备扎实的计算机科学基础知识，熟悉数据结构、算法、编程语言等。
• 熟悉至少一种图数据库系统（如Neo4j、AWS Neptune），熟练使用一种图数据库语言（如Cypher或Gremlin等）。
• 熟悉 Python 或其他编程语言: 能够熟练使用 Python 或其他编程语言进行代码编写和开发。
• 有相关知识图谱项目经验: 参与过 NLP / KG相关的项目开发，例如聊天机器人、问答系统等。
• 熟悉NLP相关技术方案（如实体识别、关系抽取等）者加分。
• 熟悉Linux操作系统者加分。
• 良好的学习能力和解决问题的能力: 能够快速学习新知识和技术，并能够独立解决问题。
• 良好的沟通能力和团队合作能力: 能够与团队成员有效沟通，并协作完成项目任务。