Algorithm Engineer, Anti-fraud
2 weeks ago
Department Engineering and Technology
LevelEntry Level
LocationSingapore
The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.
About the Team:
The Shopee E-commerce Anti-fraud Algorithm Team is dedicated to enhancing user experience by preventing risks such as low-quality products and fraudulent transactions across search, recommendation, and advertisement scenarios. We are committed to building an industry-leading risk control system that leverages cutting-edge technologies, large-scale deep learning, and emerging AI models.
If you are passionate about e-commerce and risk control, we welcome you to join us in developing advanced anti-fraud algorithms that protect our users and sellers while driving sustainable business growth.
Job Description:
As an Anti-fraud Algorithm Engineer, you will:
- Algorithm Development: Assist in designing and developing algorithms to identify fraud and abnormal transactions, ensuring user and merchant protection.
- Model Optimization: Support exploration and optimization of risk control models to improve accuracy, recall, and scalability.
- Data Analysis: Analyze transaction data, user behavior, and product/merchant information using anomaly detection and machine learning techniques.
- Risk Monitoring: Contribute to building monitoring systems to quickly detect and address risks in real time.
- Innovation & Learning: Stay updated on the latest advances in anomaly detection, reinforcement learning, and large-scale AI models, and explore ways to apply them.
Requirements:
- Bachelor's degree or above in Computer Science, AI, Data Science, or related field (graduating from December 2025 to May 2026).
- Strong programming skills; proficient in Python, C++, or similar languages.
- Solid understanding of data structures, algorithms, and basic machine learning principles.
- Familiarity with at least one deep learning framework (e.g., TensorFlow, PyTorch, MXNet) is a plus.
- Passion for applying algorithms to solve real-world risk control problems in e-commerce.
- Detail-oriented, quick learner, and strong sense of ownership.
- Good teamwork and communication skills.
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