Data Engineer Graduate (TikTok Recommendation Ecosystem Architecture) - 2027 Start (PhD)

Role Summary

Team Introduction

Our Arch-Data Ecosystem team plays a crucial role in the data ecosystem of the TikTok Recommendation System, focusing on creating offline and real-time data storage solutions for large-scale recommendation, search, and advertising businesses, serving over 1 billion users. The core goals of the team are to ensure high system reliability, uninterrupted service, and smooth data processing. We are committed to building a storage and computing infrastructure that can adapt to various data sources and meet diverse storage requirements, ultimately providing efficient, cost-effective, and user-friendly data storage and management tools for the business.

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.

Responsibilities

Building a unified infrastructure that integrates the "training data base" and "training/inference state system" for multimodal foundation models in search, recommendation, and advertising scenarios. Through collaborative optimization of data lakes, caching, distributed computing, and GPU IO, we aim to reduce training and inference costs for foundation models while improving iteration efficiency.

• Design and implement real-time and offline data architecture for large-scale recommendation systems.
• Build scalable and high-performance streaming Lakehouse systems that power feature pipelines, model training, and real-time inference.
• Collaborate with ML platform teams to support PyTorch-based model training workflows and design efficient data formats and access patterns for large-scale samples and features.
• Own core components of our distributed storage and processing stack, from file format to stream compaction to metadata management.

Requirements

• IIndividuals who are completing or have recently completed a PhD degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline.
• Experience building large-scale distributed systems, preferably in storage, stream processing, or ML infrastructure.
• Understanding of Apache Flink internals, with hands-on experience in state management, connectors, or UDFs.
• Familiarity with modern Lakehouse technologies such as Apache Paimon, Iceberg, Delta Lake, or Hudi, especially around incremental ingestion, schema evolution, and snapshot isolation.

Preferred Qualifications

• Experience in designing and optimizing Flink + Paimon architectures for unified batch/stream processing.
• Familiarity with feature storage and training data pipelines, and their integration with PyTorch, especially for large-scale model training.
• Knowledge of columnar file formats (Parquet, ORC, Lance) and how they are used in feature engineering or ML data loading.
• Proficiency in Java/Scala/C++, and strong debugging/performance tuning ability.
• Previous experience in Lakehouse metadata management, compaction scheduling, or data versioning.
• Knowledge of legacy data stores like HBase/Kudu.

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.