Job Description
The mission of this role is to comprehensively enhance the exchange's risk prevention and automated analysis capabilities through hybrid architecture, while contributing to the development of the next-generation "AI-Ready" risk control system.
Key Responsibilities
- Black Market Investigation & Graph Analysis: Utilize graph neural networks (GNN) and other algorithms to analyze massive trading behaviors and on-chain data, identifying and monitoring online fraudulent activities and high-risk address networks.
- Risk Control Strategy Assistance & Prediction: Employ AI to assist in refining risk control rules and optimizing strategies, automatically identifying vulnerabilities in existing rules, and developing forward-looking risk prediction models for proactive prevention.
- Market Manipulation & Irregular Trading Detection: Build high-concurrency, low-latency real-time monitoring and interception models for abnormal trading behaviors such as wash trading, spoofing, pump & dump, and front running.
- Real-time Anti-Fraud & Hybrid Architecture: Develop and optimize real-time risk control pipelines combining traditional machine learning with large model intent recognition to accurately intercept P2P fraud and abnormal trading groups, reducing financial losses.
- Automated Risk Control Material Review: Construct multimodal review pipelines to achieve automatic material parsing and cross-validation.
Note: We are hiring for two directions—AI Risk Control Algorithm Engineer and AI Large Model Infrastructure Algorithm Engineer. For details, please inquire via Telegram.
Job Requirements
- Education: Bachelor's or higher in CS, Statistics, Mathematics, or related fields (Master's preferred), with 5+ years of experience in risk control algorithms.
- Skills: Strong data sensitivity, ability to independently define problems and drive solutions.
- Technical Proficiency: Expertise in Python + SQL, familiarity with large-scale data processing (Hive/Spark).
- Machine Learning: Solid ML foundation, proficient in feature engineering and end-to-end model optimization.
- Graph Algorithms: Experience applying graph algorithms to black market investigation and group identification.
- Sequence Models: Knowledge of sequence models for behavioral anomaly detection.
- Real-time Systems: Experience with real-time systems (Flink/Kafka), understanding of online inference pipeline design.
- Domain Knowledge: Familiarity with at least one of the following areas: black market countermeasures (fraudulent activities/bulk attacks), trading surveillance (wash trading/spoofing), P2P anti-fraud/AML compliance.
Preferred Qualifications
- Experience in on-chain address analysis and fund tracing (e.g., Chainalysis/TRM).
- Practical experience in LLM-based risk control (intent recognition/multimodal review/RAG/workflow orchestration).
- Design experience with risk control rule engines or strategy platforms.
- Understanding of order book mechanisms and market microstructure.
- Background in risk control at top-tier exchanges or large fintech platforms.
- Publications in top conferences like KDD/AAAI/WWW.
Benefits
Negotiable
