Responsibilities
Our team is responsible for developing state-of-the-art CV/NLP/ML algorithms and strategies to improve user consumption experience, inspire merchants' service quality and revenue, and build a fair and flourishing ecosystem on our E-commerce Platform. More specifically, our team is responsible for the algorithms of Product Knowledge Graphs under TikTok's global e-commerce business. What you will do:
• Participate in the development of massive knowledge graphs of real-world products to support feed ranking, recommendations, and ads.
• Collaborate with product managers, data scientists, and the product strategy & operation team to define product strategies and features. Responsibilities:
• Knowledge graph construction, including product/content/feedback understanding and category/brand/SPU construction.
• Explore the implementation of Knowledge Graph and Cognitive Graph on the e-commerce side of TikTok e-commerce shopping guide.
• Responsible for the mining of e-commerce shopping guide knowledge such as shopping scenes/people/goods matching/product layering.
• Responsible for the optimization and iteration of computer vision related models in the e-commerce scene, including fine grain classification, product object recognition, product subject recognition, feature extraction, logo detection, brand recognition, etc., to optimize the merchant's product loading and unloading process.
• Responsible for e-commerce short video and livestream classification, multi-modal content mining, multi-modal content understanding, optimize e-commerce short video and livestream shopping experience.
• Responsible for e-commerce image search, photo search goods, goods duplication algorithm.
• Explore the cutting-edge technology of computer vision, responsible for the iteration and evolution of the overall algorithm and system.
Qualifications
Minimum Qualifications:
• In-depth knowledge in a certain field of multimedia and computer vision, including but not limited to: image search, image/video classification and recognition, image segmentation, object detection, OCR, graph neural networks, multimodal, unsupervised and self-supervised learning, etc.; Preferred Qualifications
• Familiar with the training and deployment of one or more framework models of TensorFlow/PyTorch/MXNet, and understand training acceleration methods such as hybrid precision training and distributed training;
Job Information
[For Pay Transparency]Compensation Description (Annually)
The base salary range for this position in the selected city is $153900 - $300960 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.
