Graduate Software Engineer – Live Recommendation Architecture

TikTok; Singapore; On-site; SGD 55,000 - 85,000; Full time

Job summary

TikTok is seeking a Software Engineer Graduate for the Live Recommendation Architecture (2027 Start) in Singapore. You will join a team that builds scalable, high-performance systems to support live broadcast recommendations, with opportunities to work across data pipelines, storage, and ML-enabled insights.

As a graduate, you will tackle challenging problems, contribute to cutting-edge algorithms, and grow with a global team. Onboarding by year-end is expected.

Qualifications

• Bachelor's or Master's degree in AI, software development, CS, CE or related discipline.
• Experience programming in C, C++, Java or Golang.
• Strong communication, ownership and drive.
• Familiar with big data frameworks such as Hadoop, Hive, Flink, Spark, Kafka, HBase, Redis, RocksDB, Elasticsearch.

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 for real-time streaming scenarios.
• Create globalized large-scale recommendation systems for live broadcast use cases.
• Ensure production system stability via troubleshooting, mechanism design and tooling development.
• Develop data analytics and visualization capabilities to transform raw data into insights.
• Apply data mining, ML and NLP techniques to extract insights from large-scale datasets.

Skills

C/C++/Java/Golang

Education

Bachelor's/Master's in CS/CE/AI/Software

Tools

Hadoop

Hive

Flink

Spark

Kafka

HBase

Redis

RocksDB

Elasticsearch

Job description

TikTok is seeking a Software Engineer Graduate for the Live Recommendation Architecture (2027 Start) in Singapore. You will join a team that builds scalable, high-performance systems to support live broadcast recommendations, with opportunities to work across data pipelines, storage, and ML-enabled insights.

As a graduate, you will tackle challenging problems, contribute to cutting-edge algorithms, and grow with a global team. Onboarding by year-end is expected.