Graduate Software Engineer — Live Tech, Growth & Stock Options

TIKTOK PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Benefits offered by this job

Stock options

Flexible hours

Career growth

Paid leave

Flat organization

100M+ users

Job summary

TikTok is seeking graduates to join the Live Recommendation Architecture Team to build and optimize the live broadcast recommendation system. You will contribute to stable, high-performance online services and scalable data pipelines for real-time experiences.

As part of a global, diverse team, you will work with machine learning engineers, explore big data frameworks, and apply NLP techniques to extract insights from large-scale datasets, with opportunities for growth and impact.

Qualifications

• Degree in AI, software development, CS, CE or related field
• Experience programming in C, C++, Java or Golang
• Strong communication and ownership/drive
• Familiar with open source big data frameworks (Hadoop/Hive/Flink/Spark/Kafka/HBase/Redis/RocksDB/ElasticSearch)
• Familiar with Java and C++ for big data roles

Responsibilities

• Build and maintain high-performance online services and data pipelines for TikTok Live recommendation systems
• Design and develop high-performance computing frameworks and storage systems to support real-time live streaming scenarios
• Build globalized large-scale recommendation systems for live broadcast use cases
• Ensure production system stability through troubleshooting, mechanism design, and tooling development
• Develop data analytics and visualization capabilities to transform raw data into actionable insights
• Apply data mining, machine learning, and NLP techniques to extract insights from large-scale datasets

Skills

Programming languages (C/C++, Java, Go

Communication skills

Problem solving

Education

Bachelor's or Master's in AI/CS/CE or related field

Tools

Hadoop

Hive

Flink

FlinkSQL

Spark

Kafka

HBase

Redis

RocksDB

ElasticSearch

Job description

TikTok is seeking graduates to join the Live Recommendation Architecture Team to build and optimize the live broadcast recommendation system. You will contribute to stable, high-performance online services and scalable data pipelines for real-time experiences.

As part of a global, diverse team, you will work with machine learning engineers, explore big data frameworks, and apply NLP techniques to extract insights from large-scale datasets, with opportunities for growth and impact.