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Open nowPosted 33 days ago

【校招】代码预训练数据研究工程师-大模型中心

aicarrier/522799209 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【校招】代码预训练数据研究工程师-大模型中心aicarrier/522799 · Shanghai, Chinese Mainland

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Share of postings closed within
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  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 33 days ago

The posting

1.负责代码预训练数据的质量研究、数据策略实现、训练验证和版本化交付； 2.与数据中心团队合作，定义并验收 file-level 代码 preprocessing substrate，包括语言识别、SHA256/MinHash 去重、语法解析、文件分类、reject reason 和数据版本接口； 3.建设代码质量评价体系，包括 LLM teacher 标注和质量 rubric、回归 scorer、ranker 或轻量分类器、代码可读性/正确性/完整性/复杂度及教育价值评估等； 4.借鉴 Seed-Coder、Nemotron 等公开方法，验证 heuristic filtering、LLM scorer 和 soft weighting 等方案的训练效果； 5.研究被过滤代码数据中的 false rejection，探索修复、重新组织、重评分或转换为其他数据形态后对预训练的价值； 6.建设代码 benchmark contamination 检测方案，覆盖 EvalPlus、MultiPL-E、MBPP、CRUX-O 等评测； 7.设计并执行代码数据消融及 proxy training 实验，评估代码数据对 Coding、Reasoning、Math/STEM 及 General 能力的影响。

1.计算机科学、人工智能、软件工程等相关专业硕士及以上学历； 2.熟悉 Python，并能够阅读和处理多种主流编程语言； 3.理解 AST、parser、Tree-sitter、代码去重、FIM 和 repository/file 数据结构； 4.具有 LLM batch inference、数据评分、模型训练或数据消融实验经验； 5.能够在不完整基础设施条件下快速实现研究原型，并与工程团队协作完成规模化； 加分项：参与过代码大模型预训练或代码语料建设；熟悉 Seed-Coder、StarCoder、The Stack、OpenCoder 或 Nemotron Code 数据方法；具有代码执行、编译、单元测试或沙箱环境经验；具有合成代码、代码重写或跨语言转换数据经验。

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