Led in large model application projects.
1. System architecture design and optimization: With rich experience in traditional IT system architecture design, I lead the construction and maintenance of microservice architecture to ensure high availability, high performance and scalability of the system; Use profound experience in system tuning to monitor and optimize system performance in an all-round way to ensure stable and efficient system operation. Proficient in using all kinds of middleware (such as MySQL, Redis, etc.) to provide solid technical support for system data storage and cache.
2. Application and development of multi-modal large model: use multi-modal large model or image recognition technology to accurately extract and identify design drawings and realize automatic generation of front-end code; Actively explore and deeply apply the latest multimodal large models, such as LLava1.6, Qwen-VL, VisualGLM, etc., and constantly optimize the efficiency and quality of code generation; Work closely with UI/UX designers to understand the design intent, and work with front-end developers to ensure that the generated code is functionally and visually consistent with the project requirements.
3. Application of target detection technology: With YOLO experience in traditional small models, I can use YOLO algorithm to carry out target detection tasks, optimize and improve the YOLO model, improve the accuracy and speed of detection, and make it better serve actual business scenarios, such as precise positioning of key elements in design drawing recognition.
1. Educational background: Master's degree or equivalent in computer science, artificial intelligence, data processing and other related fields.
2. Technical experience: research experience in deep learning, machine learning, natural language processing and other related fields; In-depth understanding of multimodal large model technology, familiar with the structure and principle of Vision-Transformer, CLIP, UniLM and other models; Experience in generating code based on large models, such as Codex, CodeFormer, etc. Master large model deployment and finetune technology, and be able to optimize models according to actual business scenarios; Proficient in YOLO tuning methods, with experience in using YOLO series models for real project development.
3. Ability and quality: good communication skills, able to accurately convey technical solutions and requirements in cross-department cooperation; Have excellent team work spirit, actively participate in team discussion and collaboration, to solve technical problems together; Have excellent team leadership, can effectively lead the team to carry out technical research and development work, including but not limited to making team work plan, reasonably allocating tasks, guiding team members to technical growth, solving internal collaboration problems, etc., to ensure timely and high-quality project delivery.
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