Data Engineer Graduate (TikTok Recommendation Ecosystem Architecture) - 2027 Start (PhD)
Core
Design and implement real-time and offline data architecture for large-scale recommendation systems, building unified infrastructure for multimodal foundation models in search, recommendation, and advertising.
Role type
Senior IC data engineer (distributed systems & ML infrastructure)
Builds
Scalable streaming Lakehouse systems, distributed storage and processing stack, feature pipelines for model training and inference
Domain
Internet / Recommendation Systems / Distributed Data Infrastructure
Deliverable
production ML models
Required skills
Large-scale distributed systems design, Apache Flink internals, Lakehouse technologies (Paimon, Iceberg, Delta Lake, Hudi), PyTorch integration, Java/Scala/C++, columnar file formats (Parquet, ORC, Lance)
Preferred skills
Flink + Paimon architecture optimization, Lakehouse metadata management, legacy data stores (HBase/Kudu)
Technologies
Apache Flink, Apache Paimon, Apache Iceberg, Delta Lake, Hudi, PyTorch, Parquet, ORC, Lance, HBase, Kudu
Responsibilities
Design real-time and offline data architecture for large-scale recommendation systems; Build scalable streaming Lakehouse systems; Collaborate with ML platform teams to support PyTorch-based model training workflows; Own core components of distributed storage and processing stack
Seniority
PhD level, Senior IC
