Big Data Engineer: Scalable ML & Recommendation Infra

TIKTOK PTE. LTD.; Singapore; Vor Ort; SGD 120.000 - 160.000; Vollzeit

Benefits dieser Stelle

Positive team atmosphere

Career growth opportunity

Paid leave

Zusammenfassung

TikTok is expanding its E-commerce Recommendation Infra team to build and optimize the infrastructure for recommendation systems powering TikTok Shop. You will work with ML engineers to create scalable, high-availability data pipelines and storage systems that handle massive datasets.

The role emphasizes designing robust data architectures, implementing scalable storage and computing solutions, and applying ML techniques to derive actionable insights for the platform.

Qualifikationen

• Bachelor's degree in computer science, software engineering, or related field.
• Familiar with major open source big data frameworks (Hadoop, Hive, Flink, Spark, Kafka, HBase, Redis, ElasticSearch).
• Proficient in Java, C++, and other programming languages.
• Strong coding and troubleshooting ability.

Aufgaben

• Design offline data architecture for large-scale recommendation systems.
• Design and implement scalable, stable storage and computing systems.
• Troubleshoot production systems and ensure stability of operations.
• Build distributed storage and computing infrastructure for massive data.
• Develop analytics apps and use data-oriented languages and visualization tools.
• Apply data mining, NLP, and machine learning to extract insights from large datasets.
• Visualize, interpret, and report data findings.

Kenntnisse

Java

C++

Troubleshooting

Big data concepts

Ausbildung

Bachelor's degree in CS or related field

Tools

Hadoop

Hive

Flink

Spark

Kafka

HBase

Redis

ElasticSearch

Jobbeschreibung

TikTok is expanding its E-commerce Recommendation Infra team to build and optimize the infrastructure for recommendation systems powering TikTok Shop. You will work with ML engineers to create scalable, high-availability data pipelines and storage systems that handle massive datasets.

The role emphasizes designing robust data architectures, implementing scalable storage and computing solutions, and applying ML techniques to derive actionable insights for the platform.