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

TikTok; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

TikTok Singapore is seeking a PhD-qualified engineer to help build the Arch-Data Ecosystem for large-scale data storage and ML infrastructure. You will design real-time and offline data architectures for recommendation, search, and advertising workloads, collaborating with ML platform teams.

This role involves optimizing lakehouse storage, managing metadata, and advancing streaming and batch processing with Flink and modern lakehouse technologies.

Qualifications

• PhD in AI, CS, software development or related field.
• Experience building large-scale distributed systems (storage/ML infra).
• Understanding of Flink internals and state management.
• Familiar with Lakehouse tech (Paimon/Iceberg/Delta Lake/Hudi).

Responsibilities

• Design real-time and offline data architecture for large-scale recommendation systems.
• Build scalable streaming Lakehouse systems powering feature pipelines and real-time inference.
• Collaborate with ML platforms to support PyTorch training workflows and data formats.
• Own components of distributed storage and processing stack from file formats to metadata.

Skills

Distributed systems

State management

Flink internals

Model training pipelines

PyTorch integration

Education

PhD in AI/CS/Software

Tools

Apache Flink

Paimon

Iceberg

Delta Lake

Hudi

Parquet

ORC

Lance

HBase

Kudu

Java/Scala/C++

Job description

Discover a career that energizes and excites you every day.

@2026 TikTok

Location:

Employment Type:

Regular

Job Code:

A44785A

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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 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.

ResponsibilitiesBuilding 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.

Qualifications

Minimum Qualifications:

• 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.

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.