职位描述 Job Description： 该岗位隶属于深度学习团队，面向模型研发与生产应用场景，负责核心数据与特征体系的建设，优化和维护，为模型训练和落地提供稳定，高质量，可扩展的数据支持。你将参与深度学习建模相关数据的全流程研发与建设，面向模型需求设计和优化数据组织，特征表达及内容体系，保证和提升数据系统的可靠性，时效性与可扩展性。 This role is key part of the Deep Learning team and is responsible for the development, optimization, and maintenance of the core data and feature infrastructure that supports model development and production deployment. The position provides stable, high-quality, and scalable data support for model training and online trading. You will contribute to the end-to-end development of data systems for deep learning workflows, designing and refining data organization, feature representation, and content structures to meet modeling needs, while improving the reliability, efficiency, and scalability of the overall data platform. 岗位职责 Your Role： 1. 负责深度学习建模相关核心数据与特征链路的设计，开发，优化和维护 Design, implement, optimize, and maintain core data and feature pipelines for deep learning applications 2. 建设稳定，可扩展的数据处理与特征生产体系，支持模型训练，研究迭代与生产落地 Develop, robust, high-performance, and scalable data processing and feature generation systems to support model training, rapid research iteration, and production deployment 3. 与建模，研究，工程及上游数据团队紧密协作，理解需求并提供高质量的数据解决方案 Partner cross-functionally with modeling, research, engineering, and upstream data teams to translate business and technical requirements into scalable, high-quality data solutions 4. 持续提升数据的准确性，一致性，完整性与时效性，推动数据质量监控，验证与管理机制建设 Drive continuous improvements in data accuracy and completeness, and establish robust processes for data quality valiadtion and monitoring 职位要求 1. 毕业于国内外知名高校的计算机，软件工程，数学或相关专业本科及以上学历 Bachelor's degree or higher in Computer Science, Software Engineering, Mathematics, or a related discipline 2. 精通数据结构与算法，具备扎实的C++/C语言及Python编程能力与计算机科学基础 Strong background in computer science, with solid programming proficiency in C++/C and Python 3. 具备良好的沟通协作能力与书面表达能力 Excellent written and verbal communication skills 4. 认真细致，责任心强， 能够持续处理复杂且细节密集的数据问题，并对数据质量保持严谨判断 Detail-oriented, highly responsible, and capable of handling complex, detail-intensive data challenges with strong judgment and a high standard for data quality