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Computer Vision Algorithm Engineer
1 month ago
At TikTok, we're 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.
We're seeking a talented Computer Vision Algorithm Engineer to join our team. As a key member of our e-commerce business, you'll be 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.
Key Responsibilities:
- 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.
- 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.
Requirements:
- 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.
- 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.
We're committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at [insert contact information].
