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Open nowPosted 31 days ago

【校招】Coding 方向青年研究员-大模型中心

aicarrier/522799209 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【校招】Coding 方向青年研究员-大模型中心aicarrier/522799 · Shanghai, Chinese Mainland

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The clock on this job

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11.8% 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. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 31 days ago

The posting

1.面向真实软件研发任务，研究 Coding Agent 的核心方法，提升模型在仓库级理解、长程任务执行、工具使用、错误修复和持续学习等方面的能力，推动算法、数据、环境、训练和评测形成完整闭环； 2.研究代码理解、生成、推理和软件工程任务的关键算法，以及仓库级长上下文建模、任务规划、工具使用和多智能体协作； 3.研究基于 SFT 与强化学习的后训练方法，提升模型的推理和执行能力； 4.建设高质量代码数据的生产、清洗、配比和质量控制体系，研究合成数据、执行反馈数据及长程 Agent 轨迹的构造方法； 5.建设覆盖代码生成、仓库级开发和真实软件工程任务的评测体系； 6.建设支持 Coding Agent 训练、Rollout 和评测的环境 Infra，推动模型在真实研发场景中的稳定、高效部署与应用； 7.提出具有原创性和实际价值的研究课题，产出高水平论文、模型、Benchmark、开源系统或技术报告。

1.计算机科学、人工智能、数学、统计学或相关专业硕士及以上学历，博士优先； 2.在大语言模型、智能体、强化学习或机器学习系统方向有系统积累，对 Coding Intelligence 方向有浓厚兴趣和深入理解； 3.具备优秀的编程能力，熟练掌握 Python、PyTorch 等深度学习框架； 在以下至少一个方向有突出成果： A. Coding 模型与 Agent：代码大模型的预训练/后训练原理、Coding Agent 框架、工具调用/执行反馈机制； B. Coding 数据与强化学习：代码数据合成、SFT/PPO/GRPO、奖励建模； C. 训练、环境与评测 Infra：分布式训练、高性能推理、代码执行环境、容器/沙箱基础； 加分项：在代码生成、程序分析或 Coding Agent 方向发表过论文或有 GitHub 活跃项目、主导过代码模型/Coding Agent 相关项目、参与过有影响力的大模型/开发工具开源项目。

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