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Open nowPosted 30 days ago

【实习】大模型算法实习生（AI Agent 方向）-智能体系统中心

aicarrier/522799209 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【实习】大模型算法实习生（AI Agent 方向）-智能体系统中心aicarrier/522799 · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 30 days ago

The posting

1、面向科学领域的论文、技术报告、专业文档、知识库等异构数据，参与领域任务轨迹、数据集及 Benchmark 的构建，建设可规模化的 Agent 训练环境与评测体系。 2、聚焦高价值科学领域，提升大模型的 Agentic 能力，使模型在高复杂度任务中的表现达到行业前沿水平。重点提升模型在科学领域长程任务、多工具调用、真实环境交互中的规划、执行与反思能力。 3、探索面向长程、多轮、稀疏奖励场景的后训练算法，系统性解决信用分配、训练稳定性、探索效率等核心问题。 4、探索“AI 加速 AI 研发”的新范式，让模型参与递归数据生成、模型后训练机制迭代等研发流程，形成可递归的能力增益回路。

1、具备扎实的机器学习与深度学习基础，对大模型训练流程，尤其是后训练阶段有深度理解。 2、具备探索欲，逻辑分析能力，数据敏锐度和算法实现能力，能够将算法思路高质量落地到实际训练与评测系统中。 3、理解并能够解决大模型后训练中的关键问题，包括但不限于 Reward Hacking、Training Stability、Exploration Efficiency、长程信用分配、环境噪声、非 policy 负向 reward、训推一致性等真实工程挑战。 4、每周可实习不少于 4 天，连续实习 4 个月以上；能够稳定实习 6 个月及以上者优先。优先考虑非 2027 届应届毕业生。

【加分项】 1、在 NeurIPS、ICLR、ICML、CVPR、ACL 等顶级会议发表过高水平研究成果，或主导过知名开源项目者优先。 2、熟悉大规模后训练流程者优先，包括 rollout / 采样加速、sandbox、trajectory replay、训推框架等。 3、具备 Agent harness、可验证环境构建、复杂任务评测系统搭建经验者优先。

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