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Company Overview
A leading destination for short-form mobile video. Their mission is to inspire creativity and bring joy. They have global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul, and Tokyo.
Job Title: Machine Learning Engineer, Business Integrity
Responsibilities:
Be responsible for content understanding of commercial products, such as ads, e-commerce, short video, and live streaming.
Be responsible for data mining, feature engineering, and building scalable machine learning models to establish monetization ecology.
Optimize computational efficiency and improve stability of machine learning models to deal with billion scale business data.
Based on business data, explore and implement various cutting-edge technologies, such as pre-training, self-supervised learning, few-shot learning, etc.
Explore state-of-the-art AIGC techniques and build a new generation of AIGC-based monetization ecology systems.
Qualifications:
Bachelor’s degree or above, majoring in Computer Science, Computer Engineering, Electrical Engineering, or other related fields.
Have a solid foundation with common machine learning related techniques and algorithms (e.g. classification, clustering, regression, etc.). Be proficient with at least one deep learning framework (e.g. PyTorch,TensorFlow).
Related experience in at least one of the following areas:
Be familiar with computer vision related tasks. Have rich experience in at least one aspect, such as image/video classification, object detection, image/video retrieval, OCR, image segmentation, etc.
Be familiar with NLP-related tasks. Have experience in at least one aspect, such as text classification, semantic analysis, sentiment analysis, NER, etc.
Be familiar with audio-related tasks. Have experience in at least one aspect, such as ASR, AED, LID, etc.
Be familiar with multimodal machine learning, large-scale multimodal pre-training, etc.
Be familiar with the theory and application of graph networks, knowledge graphs, and have relevant experience.
Be familiar with model acceleration techniques such as pruning, quantization, distillation, etc.; Have relevant experience in deploying models using frameworks such as TensorRT.
Solid programming foundation. Be familiar with basic data structures and algorithms.
Have excellent analytical and problem-solving skills, logical thinking skills, communication and collaboration skills. Maintain curiosity about new things, and have a strong sense of responsibility, integrity and reliability.
Having published papers in top AI conferences or journals (CVPR, ICCV, ECCV, TPAMI, IJCV, ICML, NeurIPS, ICLR, ACL, EMNLP, NAACL, etc.) is a plus.
Being familiar with generative models is a plus, such as GPT, Stable Diffusion, etc.
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