Multimodal Large Language Model Intern
Multimodal Large Language Model Intern
多模态大模型实习生
We are seeking interns for our multimodal large language model team to develop surgical multimodal language models and validate them in medical surgical scenarios. Candidates should have strong theoretical and practical foundation in at least one of the following areas: multimodal learning, natural language processing, or computer vision. Experience with Hugging Face, LLaVA, and vision projects like MMCV and YOLO is preferred. We particularly welcome candidates with strong hands-on practical abilities.
Job Responsibilities:
1. Develop multimodal foundation models involving video and text modalities
2. Research and develop technical solutions for integrating various surgical tasks and downstream task transfer in medical surgical scenarios
3. Implement project solutions, conduct code reviews, and perform acceptance testing
Job Requirements:
1. Master's degree or above preferred, in related fields such as Artificial Intelligence, Computer Science, Communications, Automation, Mathematics, etc.
2. Strong foundation in natural language processing or multimodal learning; familiarity with foundation model projects like Hugging Face, LLaMA, BLIP, LoRA is preferred
3. Strong programming skills and practices; proficiency in either Python or C++; experience with Linux development environment
4. Proficiency in mainstream deep learning frameworks such as PyTorch; experience with model deployment tools (tensorRT, Trition, etc.) is a plus
岗位职责:
1. 负责开发多模态大模型 (Foundation Models),涉及视频和文本等模态;
2. 结合医疗手术场景,研发多种手术任务整合和下游任务迁移的技术方案;
3. 负责相关项目方案的实施部署、代码审核及验收。
岗位要求:
1. 硕士及以上学历优先,人工智能、计算机、通信、自动化、数学等相关专业;
2. 具有较好的自然语言处理或多模态学习的基础,熟悉Hugging Face、LLaMA、BLIP、LoRA等基础模型项目者优先;
3. 具有较强的编程能力和素养,熟悉算法设计。熟悉Python、C++中至少一种编程语言,熟悉Linux环境开发;
4. 熟悉PyTorch等主流深度学习框架。熟悉相关模型部署工具(tensorRT、Trition等)者优先。
Interested candidates please send your CV and relevant materials to hr02@cair-cas.org.hk and indicate the position you are applying for.
感兴趣请发送简历到:hr02@cair-cas.org.hk 并注明申请的职位