IT Intern- LLM

thin 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 (e.g., Qianwen, GLM, LLMA).

• Proficient in Python programming and familiar with at least one deep learning framework (e.g., 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。

Job Systems/Information Technology

Organization Cummins Inc.

Role Category Hybrid

Job Type Student - Internship

ReqID 2403424

Relocation Package No