AI Data Engineer , Marketplace Intelligence & Data (2027 Graduate)

Shopee; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Shopee is seeking a data-engineering oriented specialist to build end-to-end data systems that empower AI models and applications. You will design scalable data infrastructure, ingest and curate large datasets, and collaborate with product and research teams across the marketplace.

The role emphasizes rigorous data quality, experimentation, and rapid iteration of models through data loops, with exposure to multimodal data and foundational AI capabilities.

Qualifications

• Bachelor's degree in CS, SE, DS, statistics, or related field.
• Strong Python and Java, plus solid SQL and data structures/algorithms.
• Experience with Spark, Flink, or Ray for big data processing.
• Familiarity with large models, multimodal data, or AI governance is a plus.

Responsibilities

• Design and implement scalable data infrastructure covering storage, ingestion, cleaning, labeling, and analysis.
• Develop multimodal data strategies and pipelines to support large-model development.
• Collaborate with AI teams to build a data–model–evaluation loop for rapid iteration.
• Stay updated on new data processing techniques and apply them to business needs.

Skills

Python

Java

SQL

Data structures & algorithms

Communication

Education

Bachelor's degree in CS/Software Eng/DS/Statistics or related field

Tools

Spark

Flink

Ray

SQL engines

Job description

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.

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.

Job Description

In a data-driven and evaluation-driven manner, build an efficient closed loop for data iteration and establish an end-to-end data system spanning data sourcing, labeling, processing, synthesis, and evaluation. Continuously build high-quality datasets and evaluation sets to keep improving foundation model capabilities and to drive the development of AI models and applications.

Responsibilities Cover One Or More Of The Following Directions

• Design and implement high-performance, scalable, and distributed data infrastructure covering the full lifecycle — data storage, ingestion, cleaning, labeling, management, and analysis — and continuously improve data engineering efficiency.
• Design audio-visual multimodal training data strategies; develop efficient data processing, synthesis, and optimization operators and pipelines, and build a multimodal data asset repository to meet the data needs of large model development.
• Build a "data–model–evaluation" closed loop together with Agents, using data to drive rapid iteration of large models.
• Track cutting-edge techniques and methods in the large-model data domain, explore innovative approaches such as data augmentation, data distillation, and high-quality data filtering, and land them in real business scenarios to increase data value.

Requirements

• Bachelor's degree or above in Computer Science, Software Engineering, Data Science, Statistics, or a related field.
• Solid programming fundamentals; proficient in Python and Java, competent in SQL; strong command of common data structures and algorithms.
• Familiar with at least one big data processing framework (any of Spark / Flink / Ray), or strong self-learning ability backed by relevant coursework / projects.
• Familiar with the fundamentals of large models / multimodal / AIGC (LLM, Diffusion, T2V, CLIP / VLM, etc.), or having relevant side projects.
• Familiar with the fundamentals of Agents (Tool Use, trajectory, Memory, multi-turn interaction), or having worked on Agent-related projects.
• Good "data sense": able to identify data quality issues and willing to be rigorous about data accuracy.
• Good communication skills and a collaborative mindset.

Good To Have

• Experience with large-scale data processing (from coursework / internships / competitions), having handled TB–PB scale data. Familiarity with data warehouse dimensional modeling (Kimball / OneData approach).
• Experience with model evaluation / benchmarking (exposure to VBench, ELO, GSB, Langfuse, etc. is a plus).