Big Data Engineer Graduate (TikTok Global E-Commerce Recommendation & Search Architecture) - 2027 Start

Team Introduction: E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-commerce Recommendation and Search Infra team is responsible for building up and optimizing the infrastructure for such recommendation and search systems, so as to provide the best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques. The Search team is mainly responsible for the search algorithm innovation and architecture research and development of TikTok Shop. We use cutting-edge machine learning technology for end-to-end modeling and continuous innovation and breakthroughs, while focusing on the construction and performance optimization of distributed systems and machine learning systems.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities - Design and implement offline data architectures for large-scale e-commerce recommendation and search systems - Build flexible, scalable, and high-performance storage and computing systems for e-commerce big data workloads - Ensure production system stability through troubleshooting, mechanism design, and tooling development - Develop data analytics and visualization capabilities to transform raw e-commerce data into meaningful insights - Apply data mining, machine learning, and NLP to extract insights from large-scale e-commerce datasets - Optimize data pipelines for feature generation, model training, and search index construction for e-commerce scenarios