Machine Learning Engineer Graduate (Global E-Commerce, Platform Governance) - 2027 Start (PhD)
Core
PhD-level ML engineer building risk detection algorithms, graph learning platforms, and sequence models to govern e-commerce ecosystem health, identify low-quality entities, and optimize product experiences.
Role type
PhD-level Machine Learning Engineer (Platform Governance & Risk Control)
Builds
Large-scale graph storage/learning platforms, risk prediction models, and multimodal representation systems for e-commerce content and merchants.
Domain
E-commerce platform governance, risk control, and graph machine learning
Deliverable
production ML models
Required skills
Deep learning, graph neural networks, sequence learning, algorithm design, AI-agent development, theoretical ML foundation
Preferred skills
High-level conference publications, data mining, search recommendation, content understanding, governance risk control, big data tools (Hive, Spark, Hadoop)
Technologies
PyTorch, TensorFlow, DGL, pyg, sklearn, numpy, pandas
Responsibilities
Mine and predict risks/low-quality merchants/products/creators using algorithms; build data models to improve product experience and ecosystem efficiency; construct large-scale network/feature sequence models for content understanding and community mining; build graph storage and learning platforms for community governance; research and implement cutting-edge ML/graph/sequence learning technologies in production.
Seniority
PhD, Research & Hands-on IC
