Machine Learning Engineer Graduate (Global E-Commerce, Recommendation) - 2027 Start
Core
Building large-scale E-commerce recommendation algorithms and systems for live-streaming, short videos, and commodity recommendations to improve user engagement.
Role type
Graduate Machine Learning Engineer (Recommendation Systems)
Builds
Large-scale recommendation systems for E-commerce live-streaming, short videos, and commodities
Domain
E-commerce, Recommendation Systems, Large-scale Machine Learning
Deliverable
production ML models
Required skills
Applied machine learning, Deep Learning (TensorFlow/PyTorch), C++/Python, Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep
Preferred skills
Recommendation systems, online advertising, information retrieval, NLP, large-scale data mining, academic publications (KDD, NeurIPS, etc.), Kaggle/KDD-cup experience
Technologies
TensorFlow, PyTorch, C++, Python
Responsibilities
Design and develop predictive models for candidate generation and ranking (CTR/CVR), build real-time data pipelines and feature engineering, extract and transform large volumes of unstructured data, run experiments to test deployed model performance, debug production issues
Seniority
Junior, Graduate Program