Machine Learning Engineer Graduate (Global E-Commerce, Platform Governance) - 2026 Start (BS/MS)
Core
Build risk detection algorithms and data models to identify low-quality merchants, products, and creators in e-commerce scenarios, and construct large-scale graph learning platforms for community governance.
Role type
Machine Learning Engineer (Graph Learning & Risk Control)
Builds
Scalable machine learning models, graph storage platforms, and risk detection systems for e-commerce ecosystem governance.
Domain
E-commerce platform governance, risk control, graph learning, sequence modeling
Deliverable
production ML models
Required skills
Deep learning, graph neural networks, machine learning algorithms, graph modeling, node/subgraph classification, community mining, representation learning, self-supervised/semi-supervised learning, PyTorch, TensorFlow, DGL, pyg, sklearn
Preferred skills
Data mining, search recommendation, content understanding, governance risk control, numpy, pandas, Hive, Spark, Hadoop
Technologies
PyTorch, TensorFlow, DGL, pyg, sklearn, numpy, pandas, Hive, Spark, Hadoop
Responsibilities
Mine and predict risks in e-commerce scenarios using algorithms; build data models to support business operations; construct large-scale network/feature sequence models for content understanding and video management; build a large-scale graph storage and learning platform; implement cutting-edge ML/graph learning technologies in business scenarios.
Seniority
Graduate (Entry-level)
