Machine Learning Engineer Graduate (TikTok Shop Global E-Commerce, Recommendation) - 2026 Start (PhD)
Core
Building large-scale e-commerce recommendation algorithms and systems for TikTok Shop, including commodity, live-stream, and short video recommendations to improve user engagement.
Role type
PhD-level applied machine learning engineer (recommendation systems)
Builds
Large-scale recommendation algorithms and real-time data pipelines for e-commerce
Domain
E-commerce, large-scale machine learning, recommendation systems
Deliverable
production ML models
Required skills
Deep learning (TensorFlow/PyTorch), algorithm design (Collaborative Filtering, Matrix Factorization, Deep Neural Networks), C++/Python, statistics, feature engineering, model optimization
Preferred skills
Recommendation systems, online advertising, NLP, large-scale data mining, top-tier conference publications (KDD, NeurIPS, ICML), Kaggle competitions
Technologies
TensorFlow, PyTorch, C++, Python
Responsibilities
Design and develop predictive models for candidate generation and ranking, build real-time data pipelines, run experiments to test deployed model performance, debug production issues, work with software platforms for model deployment
Seniority
PhD graduate, entry-level IC