AI Feature/Computing/Storage Engineer Graduate (TikTok Recommendation Ecosystem Architecture) - 2027 Start
Core
Design and implement real-time and offline data architecture for large-scale recommendation systems, building scalable streaming Lakehouse systems to power feature pipelines and model training.
Role type
Senior IC distributed systems engineer (storage & streaming)
Builds
Scalable streaming Lakehouse systems, distributed storage and processing stack, feature pipelines for model training
Domain
Internet / Recommendation Systems / Data Infrastructure
Deliverable
production ML models
Required skills
Distributed systems design, Apache Flink internals, Lakehouse technologies (Paimon/Iceberg/Delta Lake/Hudi), PyTorch integration, Columnar file formats (Parquet/ORC/Lance), Java/Scala/C++
Preferred skills
Flink + Paimon architecture optimization, Lakehouse metadata management, Legacy data stores (HBase/Kudu)
Responsibilities
Design real-time and offline data architecture for recommendation systems; Build scalable streaming Lakehouse systems; Collaborate on PyTorch-based model training workflows; Own core components of distributed storage and processing stack
Seniority
Graduate (Entry-level IC)