岗位职责
- 负责携程旅游业务场景搜索/推荐排序端到端迭代优化，优化用户搜推体验，提升点击率、转化率等核心指标；
- 应用先进技术手段，优化召回、粗排、精排、重排等全链路算法模块，显著提升用户体验和转化效率；
- 具备项目技术Owner的能力，能够主导制定并落实团队在技术、业务等多维度发展方向；
- 对业务和技术变化有深入洞察，持续关注包括大模型在内的技术前沿进展和落地应用；
- 具备跨团队沟通协作能力，与其他团队密切合作，为用户提供卓越的旅行产品。
职位要求
- 8年及以上相关工作经验；计算机、统计学、数学、信息技术等相关专业；研究生及以上学历优先；
- 具备优秀的编码能力，扎实的数据结构和算法功底；有良好的数据敏感度，能从海量数据提炼核心结果；有丰富的数据分析、数据挖掘、效果评估的经验和能力；
- 熟悉掌握机器学习和深度学习算法，对推荐系统、搜索排序、计算广告相关领域有经验者优先；熟悉常用的算法模型，并在多目标优化、序列建模、多场景建模、生成式推荐等一个或多个方向有深入研究；精于逻辑推理、统计分析理论；
- 熟悉一种或多种编程语言Python/Java等；熟悉一种或多种主流的分布式深度学习计算框架Tensorflow/PyTorch等；熟悉Hadoop、Spark等分布式并行处理技术，熟练掌握Hive SQL语言，具备良好的代码开发能力；
- 具备一定的业务敏感度，创新精神和理论与实践相结合的能力，具有主动思考和学习的动力，乐于与业务共同成长；
- 具备出色的问题分析和解决能力，具有团队合作意识，对具有挑战性的问题充满激情；
- 积极拥抱大模型等创新技术。 Responsibilities
- Responsible for end-to-end iteration and optimization of search/recommendation ranking in Ctrip’s tourism business scenarios, enhancing user search and recommendation experience and boosting core metrics such as click-through rate and conversion rates.
- Optimize full-link algorithm modules including recall, rough ranking, fine ranking and re-ranking with advanced technical methods to significantly improve user experience and conversion efficiency.
- Capable of acting as a technical project owner, leading the formulation and implementation of the team’s development direction in technical and business dimensions.
- Possess in-depth insight into business and technological changes, and keep track of cutting-edge technological advancements and practical applications including large models.
- Strong cross-team communication and collaboration skills to work closely with other teams and deliver exceptional travel products for users. Qualifications
- 8+ years of relevant work experience; major in Computer Science, Statistics, Mathematics, Information Technology or related fields; master’s degree or above is preferred.
- Excellent coding skills with solid foundation in data structures and algorithms; strong data acumen to extract core insights from massive data; rich experience and ability in data analysis, data mining and effect evaluation.
- Proficiency in machine learning and deep learning algorithms; experience in recommendation systems, search ranking, computational advertising is a plus; familiar with common algorithm models with in-depth research in one or more directions such as multi-objective optimization, sequence modeling, multi-scenario modeling and generative recommendation; adept at logical reasoning and statistical analysis capabilities.
- Familiar with one or more programming languages (Python/Java, etc.); proficient in one or more mainstream distributed deep learning frameworks (TensorFlow/PyTorch, etc.); familiar with distributed parallel processing technologies such as Hadoop and Spark; proficient in Hive SQL with excellent code development capabilities.
- Good business acumen, innovative spirit and ability to integrate theory with practice; proactive thinking and learning motivation, and willingness to grow with the business.
- Outstanding problem analysis and solving capabilities, strong team spirit and passion for challenging problems.
- Proactively embrace innovative technologies such as large models.
