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Open nowPosted 34 days ago

【星启计划】AI基础研究算法青年研究员-基础科研平台部

aicarrier/522799209 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【星启计划】AI基础研究算法青年研究员-基础科研平台部aicarrier/522799 · Shanghai, Chinese Mainland

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Share of postings closed within
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  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 34 days ago

The posting

1.基座模型关键技术研究：研究预训练、后训练（SFT / RL）、数据筛选与合成、价值对齐、评测等关键技术，提升模型的推理、代码、智能体与多模态能力。 2.数据体系建设：构建高质量数据集（pretrain / SFT / RL / 评测集），开展数据合成、质量评估、难度控制与动态筛选，优化数据配方与训练策略。 3.架构与训练范式：参与前沿架构研究、算法验证与工程实现，优化突破 Transformer 及多模态新架构，验证大规模预训练范式。 4.评测与对齐：构建评测体系、奖励模型与自动验证器，分析失败案例，研究训练稳定性与能力退化问题。 5.工程与工具链：开发高效算法验证工具链与内部算法库，沉淀可复用的训练/推理/评测基础设施。 6.成果产出：跟踪前沿进展，开展算法复现与创新研究，发表高水平论文、贡献开源成果。

1.硕士及以上，博士优先；计算机、人工智能、计算机视觉、自然语言处理、多模态、机器学习、数学、统计等相关专业。 2.熟练掌握 Python，熟悉 PyTorch、Transformers 等框架，熟悉常用数据结构与算法。 3.掌握大模型预训练、SFT、对齐、评测完整流程，熟悉监督微调、偏好优化、强化学习、合成数据或模型自进化中的至少一个方向。 4.熟悉 DeepSpeed / Megatron / XTuner / LLaMA-Factory / vLLM / SGLang / LMDeploy / OpenCompass 等训练、推理、评测框架中至少一种。 5.有顶会论文发表，或有大模型相关经验、一线互联网公司算法研发经验、高质量开源贡献。

加分项： 1.大规模训练与部署经验，多机多卡训练经验 2.垂直领域背景（如化学、生物、材料、地球科学、物理等，熟悉 PubChem / UniProt / RDKit 等工具链） 3.Agent / Skill 开发、自动化 pipeline 落地经验 4.竞赛获奖、完整研究项目经历

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