Machine Learning Engineer Graduate (Global E-Commerce, Platform Governance) - 2026 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 (Graph/Sequence Learning)
Builds
Large-scale graph storage/learning platforms, risk prediction models, and multimodal representation systems for e-commerce governance.
Domain
E-commerce platform governance and risk control
Deliverable
production ML models
Required skills
Deep learning, graph neural networks, sequence learning, algorithm implementation, theoretical ML foundation, PyTorch, TensorFlow, DGL, pyg, sklearn
Preferred skills
Data mining, search recommendation, content understanding, governance risk control, Hive, Spark, Hadoop, numpy, pandas
Technologies
PyTorch, TensorFlow, DGL, pyg, sklearn, Hive, Spark, Hadoop, numpy, pandas
Responsibilities
Mine and predict risks/low-quality merchants/products/creators using algorithms; Build data models for 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-level, Research & Implementation
