# Agent评估方向算法实习生

External opening: you cannot apply through AI Native Match; apply on the official site.

Apply through the official channel. The full external receipt stays in your workspace. When signed in, three minimal event types explicitly recorded through the CLI are reported by default: selection, self-reported application and channel observation. Browsing or saving a role does not report an event; external applications do not appear under My applications.

- Company: 小米 (Stage unknown)
- Locations: 北京
- Role: Algorithm
- Apply on the official site: https://xiaomi.jobs.f.mioffice.cn/internship/position/7662657793955268910/detail

## Role description from source

Agent评估体系搭建与优化：
1. 负责智能Agent、大模型应用智能体的评估体系设计、搭建与迭代优化，覆盖Agent规划、工具调用、记忆交互、多轮决策等核心能力评估。

2. 从事大模型Agent评估领域前沿技术研究，探索自动化评估、客观量化评估、主观体验评测等方案的落地应用，包含评测数据集构建、评估指标体系设计、评测流程迭代优化。

3. 负责产品级智能Agent的效果评估与迭代优化，针对Agent推理错误、工具滥用、决策低效、多轮一致性差等实际问题，设计针对性评测方案与优化策略，持续提升智能Agent的综合交互与任务执行效果。

算法研究与创新：
跟踪大模型Agent、智能体评估、大模型评测领域的前沿研究成果，将先进评估算法、评测框架落地应用于公司智能Agent产品，沉淀标准化评测工具与方法论，优质成果可整理为学术论文、技术专利或技术报告对外输出。
任职要求
1. 本科及以上学历，在读研究生优先，计算机科学、人工智能、自然语言处理、大模型、智能Agent相关专业优先；
2. 在大模型评测、智能Agent、自然语言处理、大模型应用落地方面有相关实践经验者优先；
3. 熟练掌握Python编程语言，熟悉PyTorch/TensorFlow等主流深度学习框架，熟悉大模型微调、Prompt工程、Agent框架（如LangChain、AutoGPT等），了解大模型自动化评估、对抗评测、多维能力评测相关技术；
4. 做事严谨踏实、逻辑清晰、责任心强，具备良好的问题拆解、数据分析能力，拥有优秀的沟通协作能力和团队合作意识；
5. 在ACL、EMNLP、ICML、NeurIPS等国际顶级会议发表相关论文、参与过大模型评测相关竞赛并取得优异成绩、GitHub有Agent/大模型评测相关开源项目贡献者优先。
接口顶部原始条件（未做资格推断）
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---
opening_id: a943784e-9ce0-4d19-95ab-13abf3bddf4a

`anm openings save --id a943784e-9ce0-4d19-95ab-13abf3bddf4a`