Job Description
The mission of this role is to enhance the exchange's risk defense and automated analysis capabilities through hybrid architecture, contributing to the development of the next-generation "AI-Ready" risk control system.
Key Responsibilities
- Black Industry Mining & Graph Analysis: Utilize graph neural networks (GNN) and other algorithms to analyze massive trading behaviors and on-chain data, identifying and monitoring online fraud intelligence and high-risk address networks.
- Risk Control Strategy Assistance & Prediction: Leverage AI to assist in risk rule refinement and strategy optimization, automatically identifying vulnerabilities in existing risk control 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 and 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. Contact via Telegram for details.
Job Requirements
- Bachelor's or higher in CS, Statistics, or Mathematics (Master's preferred), with 5+ years of risk control algorithm experience.
- Strong data sensitivity and ability to independently define problems and drive implementation.
- Proficient in Python + SQL, familiar with large-scale data processing (Hive/Spark).
- Solid ML foundation, experienced in feature engineering and end-to-end model optimization.
- Familiar with graph algorithms for black industry mining and group identification.
- Knowledge of sequence models for behavioral anomaly detection.
- Experience with real-time systems (Flink/Kafka), understanding online inference pipeline design.
- Familiar with business logic and adversarial evolution in at least one of these areas:
- Black industry countermeasures (fraud farming/bulk attacks)
- Trading surveillance (wash trading/spoofing/pump & dump)
- P2P anti-fraud/AML compliance
Preferred Qualifications
- Experience in on-chain address analysis and fund tracing (Chainalysis/TRM).
- LLM risk control implementation experience (intent recognition/multimodal review/RAG/workflow orchestration).
- Experience designing risk control rule engines or strategy platforms.
- Understanding of orderbook mechanisms and market microstructure.
- Risk control background in top-tier exchanges or large fintech platforms.
- Publications in top conferences like KDD/AAAI/WWW.
Benefits
Negotiable
