About The Team
The mission of the Marketplace Intelligence and Data team is to build sustainable, efficient data and intelligence products that power Shopee's business growth. The team is responsible for Shopee's e-commerce data warehouse, merchant and operations data products, end-to-end traffic data, product algorithms (including product listing, governance, content optimization, SPU cataloging and price comparison), marketing algorithms (including merchant onboarding, assortment, and recommendations), review algorithms, user profiling, as well as foundational AI capabilities such as machine translation, speech processing, computer vision, and identity verification.
As the core horizontal data team supporting all algorithm teams within Marketplace Intelligence and Data, the Algo Data Team aims to be the most reliable strategic data partner for algorithm development. We are committed to delivering efficient, stable, and high-quality data services that accelerate algorithm iteration and transform data into strong commercial value for Shopee.
Job Description
As an Algorithm Data Engineer, you will be responsible for the following key areas, transforming data into algorithmic productivity:
Feature Platform & Feature Store Construction
- Lead or participate in the design, development, and maintenance of enterprise-level feature platforms / feature stores for both traditional models and LLMs. Address challenges such as online-offline feature consistency, real-time performance, and availability. Standardize and automate feature engineering pipelines to improve the efficiency of algorithm teams.
High-Quality Dataset Construction And Maintenance
- Design and build high-performance, low-latency offline and real-time datasets for model training, evaluation, and online inference scenarios. This includes pre-training dataset construction, data filtering, data quality evaluation, data augmentation, and automated evaluation pipelines.
Algorithm Experimentation And Monitoring Pipelines
- Participate in building and maintaining the core data pipelines for algorithm experiments, providing end-to-end support from data preparation, configuration, and execution monitoring to metric analysis and result interpretation.
High-Value Label And Knowledge Graph Mining
- Leverage deep understanding of e-commerce business and algorithms to mine high-value user profiles, item labels, and relationship graphs from massive behavioral data, effectively feeding back into model optimization and business strategy.
Requirements
- Currently pursuing a Bachelor's degree (or higher) in computer science , Artificial Intelligence or related fields.
- Familiar with one or more big data technologies such as Spark, Flink, Hadoop, HBase, Kafka, Druid, ClickHouse.
- Excellent logical thinking, communication, project management, and cross-team coordination skills.
- Highly self-motivated, resilient under pressure, and eager to continuously explore and drive business breakthroughs.
Preferred Qualifications
- Experience with LLM pre-training data pipelines, Data Lake, Data Flywheel, or vLLM.
- Background in model evaluation (benchmarks) and model training (pre-training) is a strong plus.
