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The team use the most advanced AI technology to combat various risks/violations in Bytedance's e-commerce platform, maintain platform security, build a good e-commerce ecosystem, and empower business teams to improve work efficiency. We pursue the ultimate risk detection capability. The fairness and sustainability of the e-commerce ecosystem, high-quality content and merchandise are areas where we are constantly striving for improvement.
- 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.
- Support the production of scalable and optimised AI/machine learning (ML) models
- Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models.
- Run experiments to test the performance of deployed models, and identifies and resolves bugs that arise in the process.
- Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm.
- Work with the relevant software platforms in which the models are deployed.
Qualifications
- Work experience in a university, industry, or government lab(s), in a role with primary emphasis on AI research.
- Minimum 3 years of work experience in related fields.
- In-depth research 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.
- 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.
- Familiar with the latest research and technical progress of model compression acceleration, including but not limited to model quantization, pruning, knowledge distillation, etc., and inference frameworks such as TensorRT.
Preferred Qualifications:
- Strong practical ability, winners in Kaggle, COCO, ImageNet, ActivityNet, ICPC, NOI/IOI and other competitions are preferred.
- Understand AutoML related algorithms, network structure or super parameter automatic search experience is preferred.
- Familiar with big data related frameworks and application of MR/Spark is preferred.
- Strong practical ability, papers published in relevant competitions and top academic conferences (such as CVPR, ICCV, ECCV, etc.) are preferred.
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.