Big Data Engineer — E-commerce Rec & Search Infra

TikTok; Singapore; On-site; SGD 50,000 - 80,000; Full time

Job summary

TikTok is seeking graduates to join its E-commerce Recommendation and Search Infra team in Singapore. You will design offline data architectures for large-scale ecommerce recommendation and search systems, and build scalable storage and compute systems for big data workloads.

You will collaborate with applied ML engineers to apply data mining, machine learning, and NLP to extract insights from vast ecommerce datasets, while optimizing data pipelines for feature generation and model training.

Qualifications

• Bachelor's or Master's degree in AI, CS, or related field.
• Familiar with open source big data frameworks.
• Proficient in Java and C++ with strong debugging skills.

Responsibilities

• Design offline data architectures for large-scale e-commerce recommendation and search systems
• Build scalable storage and computing systems for e-commerce big data workloads
• Ensure production system stability through troubleshooting, mechanism design, and tooling development
• Develop data analytics and visualization capabilities to transform raw e-commerce data into meaningful insights
• Apply data mining, machine learning, and NLP to extract insights from large-scale e-commerce datasets
• Optimize data pipelines for feature generation, model training, and search index construction for e-commerce scenarios

Skills

Big data frameworks

Java

C++

Troubleshooting

Education

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

Tools

Hadoop

Hive

Flink

Spark

Kafka

Elasticsearch

Redis

RocksDB

HBase

Job description

TikTok is seeking graduates to join its E-commerce Recommendation and Search Infra team in Singapore. You will design offline data architectures for large-scale ecommerce recommendation and search systems, and build scalable storage and compute systems for big data workloads.

You will collaborate with applied ML engineers to apply data mining, machine learning, and NLP to extract insights from vast ecommerce datasets, while optimizing data pipelines for feature generation and model training.