Algorithm Engineer, Anti-fraud (Campus Recruitment 2026)
Job Description
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
- 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.
More Info
About Company
Shopee Pte. Ltd. is a Singaporean multinational technology company that specialises in e-commerce. The company was launched in Singapore in 2015, before it expanded abroad. As of 2021, Shopee is considered the largest e-commerce platform in Southeast Asia with 343 million monthly visitors.
Skills:
Orchestration, Python, Context engineering, Embedding fine-tuning, Multi-agent LLM systems, Multi-agent collaboration, Recall ranking, RAG retrieval systems, Memory architectures, Task planning, Multi-turn dialogue management, Long-text processing, Multi-document synthesis, Quantitative evaluation systems, Tool calling, RL reward models
Skills:
Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), SGLang inference architectures, vLLM, Prompt engineering, SFT, DPO, English and Chinese communication, Agent orchestration, Memory sharing, Quantization, Evaluation pipelines, Inference optimization, Human feedback, Task decomposition, Automatic metrics