Machine Learning Engineer Intern (E-commerce-Supply Chain & Logistics) - 2025 Summer/Fall

Join the E-commerce Global Supply Chain and Logistics team at TikTok! We're enhancing the shopping experience and reducing logistics operational costs. We are seeking brilliant and motivated graduate software engineers, who are eager to apply their knowledge in machine learning (ML), operations research (OR), data mining, and statistical inference to real-world challenges. We are looking for talented individuals to join us for an internship in 2025. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at TikTok Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. It runs for 12 weeks beginning in May/June 2025 or August/September 2025 (Select May if Summer or August if Fall Please state your availability clearly in your resume (Start date, End date). Summer Start Dates: Monday, May 12 Monday, May 19 Tuesday May 27 (Memorial Day May 26) Monday, June 9 Monday, June 23 Fall Start Dates: Monday, August 11 Monday, August 25 Monday, September 8 Monday, September 22 Applications will be reviewed on a rolling basis. We encourage you to apply early. Candidates can apply to a maximum of TWO positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Responsibilities: - Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business; - Utilize e-commerce big data and deep learning models to predict end-to-end estimated time of arrival (ETA), and some logistics events such as failed delivery, delivered but not received to enhance the user logistics experience. Build logistics network knowledge graphs and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. Use NLP and LLM algorithms to handle address problems such as address verification and address suggestion; - Utilize time series forecasting techniques to predict sales at different granularities and horizons, such as warehouse-level manpower forecasting, inventory-level demand forecasting etc. We need strong machine learning and deep learning skills to detect important factors and model the relationship between the future and history; - Participate in the growth of e-commerce merchants/creators, responsible for the growth algorithm of e-commerce merchants/creators, including potential merchants/creators mining algorithm, tiering algorithm, out-reach algorithm, growth algorithm, etc. Work closely with e-commerce merchants/creators related operations and product teams to achieve the high-quality growth goal of e-commerce merchants/creators; - Combined with massive e-commerce information, through data mining and machine learning, predict the performance of products in traffic/conversion, improve the efficiency of product operation strategy and pricing/subsidy strategy, and assist in optimizing traffic distribution, to satisfy the requirements of product growth, cost optimization and some other scenarios.