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

TikTok; Singapore; On-site; SGD 17,000 - 26,000; Part time

Job summary

TikTok is offering an AI Feature/Computing/Storage Engineer Intern (TikTok Recommendation Ecosystem) for a 2027 start. This PhD internship focuses on next-generation streaming lakehouse architectures and high-throughput data storage systems to support large-scale feature pipelines.

A minimum 3-month commitment is required, with roles in Java/Scala/C++ and distributed data systems. Applicants should be pursuing a PhD in CS or related field and are expected to contribute to research, prototyping,

Qualifications

• 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 such as SIGMOD, VLDB, ICDE, SOSP, OSDI, NSDI, or equivalent conferences.

Responsibilities

• 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.

Skills

Java/Scala/C++

Distributed systems

Data management research

Education

PhD in Computer Science/Engineering/Quantitative field

Tools

Apache Flink

Apache Spark

Apache Paimon

Iceberg

Delta Lake

Job description

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

Location:

Employment Type:

Intern

Job Code:

A19941A

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Team Introduction

Team IntroductionOur 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.

Responsibilities

• 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

Minimum Qualifications

• 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

Job Information

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

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