Senior Anti-fraud Algorithm Engineer - Search, Recommendation and Ads

Shopee • Fraud Detection • Commerce • Bachelor's Degree • 2 hours ago

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Salary

≈ $77k – $165k per year (Estimated)

Location

In office (Singapore)

Seniority

Senior · 2+ years exp

Confirmed on the employer's own hiring board on Sep 24, 2026. First seen by Alion on Sep 24, 2026.

Overview

Company

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Profile match

Shopee

Shopee is a multinational technology company and e-commerce marketplace platform operating as a subsidiary of Sea Limited. The company provides a hybrid B2C and C2C digital marketplace offering retail products, integrated digital payments and financial services via ShopeePay/SeaMoney, and end-to-end logistics and fulfillment solutions through SPX Express. Headquartered in Singapore, the platform serves millions of consumers and merchant partners across Southeast Asia, Taiwan, and Latin America.

shopee.com • HQ: Singapore • Commerce • Est. 2015

Research and Develop Algorithms: Identify various fraud orders in e-commerce search and recommendation, design and develop effective risk control strategies and models to guarantee user experience and seller benefit.
Model Optimisation: Explore, innovate, and optimise risk control models to improve precision, recall, and scalability.
Data Analysis: Conduct in-depth analysis of business data, user behaviour data, and seller/item information, leveraging various anomaly detection methods for modelling.
Business and Algorithm Integration: Align risk control strategies with advertising business objectives, establish a robust anomaly monitoring system, and quickly detect and address risks.
Industry Trends Monitoring: Stay updated on the latest trends in risk control and anomaly detection technologies, exploring innovative algorithms.

Bachelor's degree or higher in Computer Science or a related field
Minimum 2 years of work experience in AI engineering or anti-fraud systems.
Hands on experience in applying or fine-tuning LLM, familiar with reinforcement learning, etc
Excellent coding abilities
Solid foundation in machine learning theory and familiar with common anti-fraud models, proficient in using deep learning frameworks, such as TensorFlow/Caffe/MXNet/PyTorch
Detail-oriented, highly organised, and quick to learn.
Strong communication and teamwork abilities.
Self-motivated, resilient under pressure, and eager to drive business breakthroughs.

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