Algorithm Engineer Intern: Live Streaming ML & Data

TikTok; Singapore; Hybrid; SGD 17,000 - 28,000; Full time

Job summary

TikTok is seeking PhD interns to join our Live Platform Intelligence team in 2026. You will help build real-time, high-performance distributed infrastructure for live streaming and contribute to product features across the lifecycle, collaborating with product managers to enhance the live experience for creators and viewers in a global context.

This internship blends hands-on learning with collaboration across data science and live content, offering exposure to models for automated operations,

Qualifications

• Currently pursuing a PhD in Computer Science, engineering quantitative field
• Familiar with commonly used machine learning and deep learning algorithms, including but not limited to DNN, NLP, CV
• Familiar with Flink, Spark, Hive etc., with big data parallel processing experience
• Excellent problem-solving and mathematical foundation including probability statistics, numerical optimization

Responsibilities

• Participate in the optimization of ByteDance LIVE business and serve the LIVE experience of billions of global users.
• Adopt cutting-edge machine learning models to improve business metrics (LIVE revenue and LIVE content quality), and bring creators/operators the ultimate experience in LIVE business.
• Deeply participate in product/business discussions, analyze and understand user behavior patterns, and provide optimization directions for improvement

Skills

Machine learning

Deep learning

Big data

Education

PhD in Computer Science or quantitative engineering

Tools

Flink

Spark

Hive

Job description

TikTok is seeking PhD interns to join our Live Platform Intelligence team in 2026. You will help build real-time, high-performance distributed infrastructure for live streaming and contribute to product features across the lifecycle, collaborating with product managers to enhance the live experience for creators and viewers in a global context.

This internship blends hands-on learning with collaboration across data science and live content, offering exposure to models for automated operations,