Machine Learning Engineer (Recommendation) - TikTok e-Commerce
Core
Building large-scale recommendation algorithms and models for TikTok's e-commerce offerings, unifying content types (products, videos, live streams) across multiple countries.
Role type
Senior IC machine learning engineer (recommendation systems)
Builds
Scalable e-commerce recommendation models and AI/ML solutions for products, short videos, and live streams
Domain
E-commerce, Recommendation Systems, Deep Learning
Deliverable
production ML models
Required skills
Deep learning, Transfer learning, Multi-task learning, Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Gradient Boosting Trees, Deep Neural Networks, C++, Python, Big Data tools (Hive, Spark, MapReduce), Deep Learning frameworks (TensorFlow, Pytorch), Data mining, Statistics
Preferred skills
Personalized recommendation, Online advertising, Information retrieval, Publications at top ML conferences (KDD, NeurIPS, etc.), Competitive programming (ACM-ICPC)
Technologies
TensorFlow, PyTorch, Hive, Spark, MapReduce, C++, Python
Responsibilities
Optimize e-commerce recommendation models at massive scales, Conduct research on content recommendation circulation and cold-start problems, Develop innovative e-commerce models and algorithms, Support production of scalable AI/ML models, Build algorithms for ETL of large volumes of realtime unstructured data, Run experiments to test deployed model performance
Seniority
Senior, hands-on IC
