Machine Learning Engineer - Payment & Risk, Global Payment

The Global Payment team of ByteDance provides payment solutions - including payment acquisitions, disbursements, transaction monitoring, payment method management, foreign exchange conversion, accounting, reconciliations, and so on to ensure that our users have a smooth and secure payment experience on ByteDance platforms. The Global Payments Compliance team's duty is to establish a comprehensive and strong compliance foundation with sanction screening, transaction monitoring, risk rating system to systematically enable business models, revenue growth, and protect executives from possible legal liabilities for ByteDance Responsibilities: - Refine payment risk feature engineering and fraud evaluation systems; - Develop universal fraud and account takeover (ATO) detection models for global payment scenarios; - Explore the application of sequence models, graph networks, and LLMs in risk control scenarios; - Develop universal machine learning models to identify cross-border and regional payment risks from a global perspective; - Optimize modeling workflows to improve development/deployment efficiency and reduce maintenance costs; - Research and apply cutting-edge machine learning algorithms within the risk control domain. Minimum Qualification(s): - Bachelor’s degree and above with majors in computer science, computer engineering, statistics, applied mathematics, data science or other related disciplines; - Solid experience with data structures and algorithms; - Familiar with at least one framework of TensorFlow / PyTorch / MXNet and its training and deployment details; - Strong coding skills in at least one of the following programming languages, e.g. Python, Java, C/C++. Preferred Qualification(s): - Minimum 3 years of relevant experience; - Experience in NLP, graph mining, or fraud detection; - Experience in credit risk, payment risk, or search/recommendation systems; - CCF A/B Papers or competition awards are preferred