Responsibilities

About the Teams E-commerce - Recommendation and Marketing E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. We are a group of applied machine learning engineers and research scientists that focus on E-commerce recommendations. We are responsible for building up and scaling our recommendation system to provide the most stable and best shopping experience for our TikTok users. E-commerce - Alliance The E-commerce Alliance team aims to serve merchants and creators in the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for TikTok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators. E-commerce - Search The Search E-Commerce team is responsible for the search algorithm for TikTok's rapidly growing global e-commerce business. We use state-of-the-art large-scale machine learning technology, the cutting-edge NLP, CV and multi-modal technology to build the industry's top-class search engine to provide the best e-commerce search experience, for more than 1 billion monthly active TikTok users around the world. Our mission is to build a world where "there is no hard-to-sell good-priced product in the world". E-commerce - Search Growth The Search Growth E-commerce team is at the forefront of developing the search recommendation algorithm for TikTok's rapidly expanding global e-commerce enterprise. Utilizing cutting-edge machine learning technology, advanced NLP, CV, recommendation, and multi-modal technology, we're shaping a pioneering engine within the industry. Our objective is to deliver the ultimate e-commerce search experience to over 1 billion active TikTok users worldwide. Our mission: to create a world where "there are no hard-to-sell, overpriced products." What You Will Do - Responsible for the build and design of optimization algorithm strategies for large-scale (10 million to 100 million products or creators' contents) e-commerce recommendation algorithm pipeline - Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently. - Design, develop, evaluate and iterate on predictive models for candidate generation and ranking(eg. Click Through Rate and Conversion Rate prediction) , including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation. - Design and build supporting/debugging tools as needed.

Qualifications

Minimum Qualifications - Bachelor above degree in computer science or relevant areas. - 3+ years of experience with a solid foundation in data structure and algorithm design, and be proficient in using one of the programming languages such as Python, Java, C++, R, etc.; - Familiar with common machine/deep learning, causal inference, and operational optimization algorithms, including classification, regression, clustering methods, as well as mathematical programming and heuristic algorithms; - Familiar with at least one framework of TensorFlow / PyTorch / MXNet and its training and deployment details,as well as the training acceleration methods such as mixed precision training and distributed training; - Familiar with big data related frameworks and application, those who are familiar with MR or Spark are preferred Preferred Qualifications: - Experience in recommendation systems, online advertising, ranking, search, 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.

Job Information

[For Pay Transparency]Compensation Description (Annually)

The base salary range for this position in the selected city is $162000 - $316800 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to 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, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.