AI Infrastructure Engineer Intern (TikTok Live Recommendation Architecture) - 2027 Start

TikTok
Singapore
Workplace: OnsiteInternshipFunction: DevOps, Cloud & InfrastructureEducation: bachelorsSkills: []

Build and optimize the live broadcast recommendation architecture for low-latency, high-availability experiences. Work with applied ML engineers to design high-throughput distributed training and inference pipelines, optimize GPU-based heterogeneous systems, and reduce memory usage, inference latency, and real-time throughput bottlenecks. Help deliver scalable storage and computing infrastructure supporting live recommendation algorithms.

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FursaFursa
TikTok
TikTok
1 day ago

AI Infrastructure Engineer Intern (TikTok Live Recommendation 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

Build and optimize the live broadcast recommendation architecture for low-latency, high-availability experiences. Work with applied ML engineers to design high-throughput distributed training and inference pipelines, optimize GPU-based heterogeneous systems, and reduce memory usage, inference latency, and real-time throughput bottlenecks. Help deliver scalable storage and computing infrastructure supporting live recommendation algorithms.
Location: Singapore
Workplace: Onsite
Employment Type: Internship
Job Function: DevOps, Cloud & Infrastructure
Seniority: Intern level

Key Responsibilities

  • •Optimize recommendation model memory usage and inference latency for live scenarios on GPU-based heterogeneous computing systems.
  • •Design and implement high-throughput distributed training and inference pipelines for live broadcast recommendation models.
  • •Perform GPU kernel profiling and performance tuning to optimize real-time inference throughput for live streaming workloads.
  • •Optimize and scale online services and offline data flow performance for live recommendation systems.
  • •Solve system bottlenecks and help reduce cost overhead while building scalable storage and computing systems.

Key Requirements

  • •Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline.
  • •Solid programming skills in C++/CUDA/Python, including basic understanding of GPU architecture and distributed training.
  • •Familiarity with deep learning frameworks and basic knowledge of recommendation systems.
  • •Experience building production-grade training and inference systems for large-scale models, especially recommendations or live streaming.
  • •Hands-on experience optimizing recommendation models for memory efficiency, latency, and throughput improvements; familiarity with distributed training frameworks (NCCL, Horovod, DeepSpeed, FSDP).
Education:Bachelor's in Computer Science, Computer Engineering, Information Systems (or related technical discipline)
Tech Stack:C++CUDAPythonGPUNCCLHorovodDeepSpeedFSDP

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