AI Feature/Computing/Storage Engineer Intern (TikTok Recommendation Ecosystem) - 2027 Start (PhD)

AI Feature/Computing/Storage Engineer Intern (TikTok Recommendation Ecosystem) - 2027 Start (PhD) at TikTok in Singapore.

Responsibilities

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 us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.
• Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
• Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).
• Successful candidates must be able to commit to at least 3 months long internship period.
• Conduct research on next-generation streaming lakehouse architectures and data processing systems for large-scale recommendation feature pipelines
• Design and implement optimized data formats and storage systems to support high-throughput deep learning model training workloads
• Develop novel data management and indexing techniques to reduce end-to-end latency of feature engineering pipelines for recommendation systems

Requirements

• Currently pursuing a PhD in Computer Science, engineering or quantitative field
• Strong programming skills in Java/Scala/C++, with research experience in distributed systems, databases, or data management
• Published research in data systems at venues including SIGMOD, VLDB, ICDE, SOSP, OSDI, NSDI, or equivalent conferences

Preferred Qualifications

• Hands-on experience with big data frameworks (Apache Flink, Spark) or lakehouse technologies (Apache Paimon, Iceberg, Delta Lake)
• Research background in columnar storage formats, vector databases, or data indexing techniques
• Strong background in machine learning systems or large-scale data processing systems

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.