# AI Agent研究员实习生-小爱

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/7681240458697345307/detail

## Role description from source

1、探索下一代Harness实现与RSI范式，从第一性原理重新设计Agent Runtime: 包括但不限于上下文工程、长程任务、工具使用、记忆等，让系统自我修正、自我迭代。
2、持续调研全球SOTA，追踪、拆解、复现全球最领先的 Harness 与智能体实现(前沿实验室产品、开源框架、顶会最新工作)，形成团队可复用的技术判断。
3、从0到1构建关键模块，独立设计并落地 Harness 的核心组件，或为 RSI 搭建所需的评估体系、reward model、Environment Scaling等。
4、Harness 与 LLM 的 co-design 和协同训练。 主导或参与面向 Harness 的模型选型、mid-training(继续预训练)与 post-training(SFT、RLHF / RLAIF / RLVR、蒸馏), 让模型和Harness作为一个系统共同优化。
任职要求
1、计算机 / AI 相关方向硕士及以上;
2、在 ICLR/NeurIPS/ICML/COLM/ACL/EMNLP 等顶会有一作或核心作者论文者优先(智能体、LLM 训练与对齐、推理、强化学习、自我改进方向)。
3、熟练 Python / PyTorch，理解大模型训练与推理全链路(分布式训练、数据管线、LLM infra)，能把想法在真实系统里跑通、测准、复现。
4、熟练掌握vibe coding 并对AI使用有自己的独特理解。
5、自驱力强，创新能力强，学习能力突出，能快速上手新技术领域。

加分项（有任意一项即可）：
1、主导或深度贡献过知名开源智能体 / LLM 框架。
2、有端到端训练大模型的一线经验(预训练 / 中训 / 后训任一阶段)。
3、RL / RLHF / RLVR 实战,或对齐、奖励建模、评测体系(eval harness)的积累。
接口顶部原始条件（未做资格推断）
{"city_list": [{"code": "CT_11", "en_name": "Beijing", "i18n_name": "北京", "location_type": 3, "mdm_code": "MDCY00000001", "name": "北京", "node_status": 1, "py_name": "beijing"}], "job_post_info": {"HighlightList": [], "JobChannelPublishList": [], "address_list": [], "city_list": [], "correlation_job_list": [], "job_level_id_list": [], "job_post_object_value_map": {}, "job_post_process_time_list": [], "recruitment_type": {"active_status": 1, "children": [], "depth": 2, "en_name": "Intern", "i18n_name": "实习", "id": "202", "name": "实习", "parent": {"active_status": 1, "children": [], "depth": 1, "en_name": "Campus", "i18n_name": "校招", "id": "2", "name": "校招", "selectability": 1}, "selectability": 1}, "storefront_list": [], "tag_list": [], "target_major_list": []}, "process_type": 2, "project_type": 3, "recruit_type": {"active_status": 1, "children": [], "depth": 2, "en_name": "Intern", "i18n_name": "实习", "id": "202", "name": "实习", "parent": {"active_status": 1, "children": [], "depth": 1, "en_name": "Campus", "i18n_name": "校招", "id": "2", "name": "校招", "selectability": 1}, "selectability": 1}}

---
opening_id: 90d800a7-a625-411d-902c-bbf71c97eafb

`anm openings save --id 90d800a7-a625-411d-902c-bbf71c97eafb`