AI Feature/Computing/Storage Engineer Graduate (TikTok Recommendation Ecosystem Architecture) - 2027 Start

TikTok
Singapore
Workplace: OnsiteInternshipFunction: Architecture & Urban PlanningEducation: bachelorsSkills: ["Collaboration","Debugging","Performance tuning"]

Work on the TikTok Data Ecosystem Team to design and implement real-time and offline data architecture for large-scale recommendation systems. Build scalable streaming Lakehouse systems for feature pipelines, model training, and real-time inference. Partner with ML platform teams to support PyTorch training workflows and define efficient data formats and access patterns. Own core distributed storage and processing components, including file formats, stream compaction, and metadata management.

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FursaFursa
TikTok
TikTok
1 day ago

AI Feature/Computing/Storage Engineer Graduate (TikTok Recommendation Ecosystem Architecture) - 2027 Start

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 12 hours agoStatus: Live

Job Summary

Work on the TikTok Data Ecosystem Team to design and implement real-time and offline data architecture for large-scale recommendation systems. Build scalable streaming Lakehouse systems for feature pipelines, model training, and real-time inference. Partner with ML platform teams to support PyTorch training workflows and define efficient data formats and access patterns. Own core distributed storage and processing components, including file formats, stream compaction, and metadata management.
Location: Singapore
Workplace: Onsite
Employment Type: Internship
Job Function: Architecture & Urban Planning
Seniority: Graduate level

Key Responsibilities

  • •Design and implement real-time and offline data architecture for large-scale recommendation systems.
  • •Build scalable, high-performance streaming Lakehouse systems for feature pipelines, model training, and real-time inference.
  • •Collaborate with ML platform teams to support PyTorch-based model training workflows and define efficient data formats and access patterns.
  • •Own core components of a distributed storage and processing stack, including file format, stream compaction, and metadata management.

Key Requirements

  • •Completing or recently completed a Bachelor's or Master's 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.
  • •Solid understanding of Apache Flink internals, including hands-on work with state management, connectors, or UDFs.
  • •Familiarity with Lakehouse technologies such as Apache Paimon, Iceberg, Delta Lake, or Hudi, including incremental ingestion, schema evolution, and snapshot isolation.
  • •Ability to program in Java/Scala/C++ and demonstrate strong debugging and performance tuning skills.
Experience:Distributed systemsStorageStream processingML infrastructureLakehouseRecommendation systems
Education:Bachelor's in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline
Skills:CollaborationDebuggingPerformance tuning
Tech Stack:Apache FlinkApache PaimonIcebergDelta LakeHudiPyTorchApache ParquetORCLanceJavaScalaC++LakehouseStreaming LakehouseHBaseKudu

Company Brief

TikTok
Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.
Industry: Digital Media
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Headquarters: Singapore, Singapore
Founded: 2016
WebsiteLinkedIn