Job description
About the team
Relying on TikTok's global e-commerce scene, the team is committed to optimizing TikTok’s global e-commerce logistics fulfillment services through technologies such as machine learning, deep learning, and operational research optimization.
Externally, it provides cheap, fast, high-quality logistics services that meet different needs for global consumers and merchants; internally, it builds an intelligent logistics system to save costs, save time, improve efficiency, and improve stability for the fulfillment of orders.
We are looking for talented individuals to join us in 2025.
As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities.
Co-create a future driven by your inspiration with TikTok.
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.
Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
-Responsible for MultiModal Content understanding of TikTok short videos, identifying various structured information related to e-commerce to meet the purchasing demands of different consumers.
-Responsible for applying technologies such as AIGC in the field of content commerce, empowering various aspects of e-commerce such as product creativity generation, generation and optimization of product materials, virtual try-on, e-commerce video generation and editing.
-Responsible for recognizing the basic attributes of products in the e-commerce scenario, improving the compliance and delivery efficiency of products, and enhancing the user's purchase experience.
-Responsible for exploring cutting-edge technologies such as computer vision, AIGC (Artificial Intelligence Generated Content), and multimodal machine learning in the field of content commerce.
Minimum Qualifications
- Final year or recent graduates in Computer Science, engineering or quantitative field.
- Have in-depth research in a certain field of MultiModal Machine Learning, Computer Vision, and NLP, including but not limited to:
a) image/video classification, detection, segmentation, action recognition, MultiModal Machine Learning pre-training, text classification, unsupervised and self-supervised learning, etc.
b) multimodal generation, such as text-to-image/video/3D generation and editing, and other related multimodal experiences, diffusion model, GAN, transformer for generation tasks.
- Familiar with the training and deployment of one or more frameworks such as PyTorch/TensorFlow//MXNet, and familiar with training acceleration methods such as mixed-precision training and distributed training.
Preferred Qualifications
- Familiar with the latest research and technological progress in model compression acceleration, including but not limited to model quantization, pruning, knowledge distillation, and inference frameworks such as TensorRT;
- Strong practical skills, priority given to those who have published papers in related competitions and top academic conferences.
Required Skill Profession
Computer Occupations
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