腾讯安全-流量风控高级算法工程师
Core
Develops risk identification models and anti-fraud systems for traffic scenarios including registration, marketing, bot detection, and account theft.
Role type
Senior IC machine-learning engineer (fraud risk control)
Builds
Real-time risk detection models, anomaly mining platforms, and decision systems for fraud prevention
Domain
Internet security / Anti-fraud / Traffic risk control
Deliverable
production ML models
Required skills
Machine learning and deep learning, Graph Neural Networks (GNN), Anomaly detection, Time-series analysis, Python, PyTorch/TensorFlow, Hive/Spark/Flink, Feature engineering, A/B testing
Preferred skills
Large language models (LLM), Federated learning, Agent-based systems
Responsibilities
Build supervised/unsupervised risk models for real-time traffic judgment; Identify fraud gangs using graph mining and community detection; Develop offline platforms for discovering new attack patterns; Design collaborative decision systems with strategy teams; Engineer model deployment for low-latency service; Analyze false positives/negatives to drive model iteration; Research and apply frontier technologies like LLMs to risk control
Seniority
Senior, hands-on IC
