• Research and develop multimodal large models based on business needs, effectively integrating different data modalities (e.g., text, images, videos) to enable intelligent multimodal applications.
• Design and optimize multimodal data fusion and alignment methods to enhance model performance across various business scenarios.
• Collaborate with product managers, data scientists, and engineering teams to translate business requirements into multimodal model solutions.
• Track and analyze the latest technological advancements and trends in the field of multimodal large models, continuously improving the company’s technical capabilities.
• Explore innovative applications of multimodal large models in real-world business contexts, such as AI-generated content, image recognition and annotation, and multimodal search.
  
  
  

• Strong logical thinking, fast-learning ability, and a team-oriented mindset with a responsible and challenge-driven attitude.
• Hands-on experience in machine learning and deep learning; candidates with experience in developing and applying multimodal large models are preferred.
• Expertise in multimodal data processing and modeling, with proficiency in relevant algorithms such as CLIP, DALL-E, and GPT-4, along with experience in their application and optimization.
• Proficiency in mainstream deep learning frameworks (e.g., TensorFlow, PyTorch) and experience handling large-scale multimodal datasets.
• Strong programming skills, expertise in Python, and a solid foundation in mathematics and statistics, with excellent analytical and problem-solving abilities.

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