IT Intern- LLM
2 months ago
DESCRIPTION
This position is not available in GPP database. Talent Acquisition team member will fill in the Posting description after intake meeting.
RESPONSIBILITIES
This position is not available in GPP database. Talent Acquisition team member will fill in the Posting description after intake meeting.
QUALIFICATIONS
Main Responsibilities:
Research existing large language models and their application scenarios, assessing their potential value to the company's business.
Assist in designing and implementing prototype systems based on LLMs to address specific corporate challenges or optimize existing processes.
Participate in cross-functional team meetings to provide insights and suggestions on how to best utilize LLM technology.
Document research findings, experimental results, and technical specifications for knowledge sharing within and outside the team.
Support the team in overcoming technical challenges encountered during project management and execution.
Qualifications:
Currently pursuing an undergraduate or graduate degree in computer science, software engineering, data science/AI, or a related field.
Solid understanding of large language models with practical experience using mainstream open-source models (, Qianwen, GLM, LLMA).
Proficient in Python programming and familiar with at least one deep learning framework (, TensorFlow or PyTorch).
Strong curiosity and self-motivation, capable of working efficiently in a fast-paced environment.
Excellent communication skills, able to clearly articulate complex technical concepts.
Familiarity with relevant technologies in large language models (LLMs): understanding the basic concepts and application frameworks of LLMs, such as Transformers, pre-trained models, prompt engineering, retrieval-augmented generation, fine-tuning, LangChain, etc.
Preferred Qualifications:
Experience winning awards or publishing papers in NLP or LLM-related competitions.
Familiarity with tools such as Hugging Face Transformers.
Awareness of the limitations and challenges of LLMs in real-world scenarios.
主要职责：
调研现有的大型语言模型及其应用场景，评估其对公司业务的潜在价值。
协助设计并实现基于LLM的原型系统，以解决具体的企业挑战或优化现有流程。
参与跨职能团队会议，就如何最好地利用LLM技术提出见解和建议。
文档化研究发现、实验结果和技术规格，以便于团队内外的知识共享。
支持团队在项目管理和执行过程中遇到的技术难题。
任职资格：
目前正在攻读计算机科学、软件工程、数据科学/人工智能或相关领域的本科或研究生学位。
对大型语言模型有扎实的理解，并能展示出使用主流开源模型（如Qianwen，GLM，LLMA）的实际经验。
具备Python编程技能，并且熟悉至少一种深度学习框架（如TensorFlow或PyTorch）。
强烈的好奇心和自我驱动力，能够在快速变化的环境中高效工作。
出色的沟通技巧，能够清晰地表达复杂的技术概念。
熟悉大语言模型 (LLM) 的相关技术: 了解 LLM 的基本概念和应用框架，例如 Transformer 、预训练模型、提示工程、检索增强生成、微调、LangChain等。
加分项：
在NLP或LLM相关竞赛中有获奖经历或发表过论文。
有使用过Hugging Face Transformers等工具的经验。
对LLM在实际场景中的局限性和挑战有一定的认识。
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