Companion learning

<p>Job Responsibilities</p><ul><li>Develop advanced deep learning models, focusing on handwritten text recognition, Chinese character error detection and semantic analysis, and improving system overall accuracy and computational efficiency.</li><li>Apply computer vision technology to process diverse handwritten inputs, model and optimize for complex scenarios such as similar characters, variant characters, and messy handwriting.</li><li>Design and improve the "stroke contrast" model architecture, enhance the ability to extract structural features of Chinese characters, and achieve high-precision similar character recognition.</li><li>Participate in the deployment, fine-tuning, and performance optimization of large language models (LLM), ensuring model stability, interpretability, and response speed in real-world applications.</li><li>Work closely with the engineering team to integrate AI models into the product production environment, and promote technical achievements to be applied in educational technology or language learning scenarios.</li><li>Based on user feedback and actual usage data, continuously iterate model performance, perform error analysis and system improvement.</li></ul><p> Work requirements</p><ul><li>Bachelor's degree or above in Computer Science, Artificial Intelligence, Data Science, or related fields.</li><li>In-depth understanding of deep learning and computer vision core technologies, familiar with mainstream architectures such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Transformer.</li><li>Applicants with handwriting recognition, optical character recognition (OCR) or natural language processing (NLP) related project experience are especially welcome.</li><li>Proficient in PyTorch or TensorFlow, etc., deep learning frameworks, with actual model development, training, debugging and deployment experience.</li><li>Have practical experience in large language model (LLM) fine-tuning, prompt engineering, quantization compression or inference optimization, and understand their evaluation metrics and risk control methods.</li><li>Applicants with enthusiasm for educational technology, Chinese language technology or intelligent learning applications will be given priority. </li><li>Have excellent logical thinking and problem-solving skills, and be able to independently complete technical research and experimental design.</li><li>Good communication and collaboration skills, able to clearly express technical concepts and effectively cooperate with cross-disciplinary teams.</li></ul>