Machine Learning Engineer, Recommendations - USDS E-commerce Alliance

Summary: TikTok USDS Joint Venture is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The role focuses on building and designing large-scale machine learning algorithms to enhance the e-commerce experience for TikTok users and improve the efficiency of merchants and creators. Responsibilities: - Build and design large-scale machine learning algorithms to model the real-time interests of creators to improve conversion efficiency - Optimize TikTok's massive commodity relationship mining and ranking and recall of creators' product recommendations, and improve the overall GMV of the platform - Use the large scale of data to deeply analyze the behavior of creators and merchants and build targeted algorithm strategies to empower creators and merchants, improve merchants' monetization efficiency, and boost industrial upgrading - Support the rapid development of TikTok's e-commerce business, serve millions of merchants, explore more efficient business models, satisfy users with the best shopping experience, and promote healthy ecological development Required Qualifications: - Bachelor's degree or higher in Computer Science or related fields - Strong programming and problem-solving ability - This role is open to graduates in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep, GBDT, LTR, Word2vec, DIN, Deep&Wide - Experience in Deep Learning Tools such as tensorflow/pytorch - Experience with at least one programming language like C++/Python or equivalent Preferred Qualifications: - Experience in recommendation system, search engine, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields - Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc Required Skills: Machine Learning, Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide, Deep Models, Learning to Rank (LTR), Deep & Wide Models, Deep Learning Frameworks - TensorFlow, Deep Learning Frameworks - PyTorch, Programming - Python, Programming - C++, Recommendation Systems, Search Engine, Online Advertising, Information Retrieval, Natural Language Processing, Large-scale Data Mining Benefits: Medical, dental, and vision insurance, A 401(k) savings plan with company match, Paid parental leave, Short-term and long-term disability coverage, Life insurance, Wellbeing benefits, 10 paid holidays per year, 10 paid sick days per year, 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)