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Open nowPosted 2 days ago

Ai infra 实习生-2028 届

vrfi1sk8a0/379481106 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen nowAi infra 实习生-2028 届vrfi1sk8a0/379481 · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

13.7% of postings close within 7 days. Measured by our own scanner across the market. vrfi1sk8a0/379481 postings stay open a median of 16 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.8%3 days
  3. 13.7%7 days
  4. 22.1%14 days
  5. 37.6%30 days
  6. 59.1%60 days
This job: posted 2 days ago

vrfi1sk8a0/379481 median: 16 days open

The posting

- 参与 MiniMax 数据、后训练与评测 Infra 研发，解决海量多模态数据处理、训练实验和模型评测中的系统问题。可结合兴趣和基础，选择一个或多个方向深入。 你将参与的工作 1. 数据平台研发：建设面向模型研发的数据平台，开发数据集、元数据、版本与血缘管理，完善数据检索、质量分析及任务管理能力，支持数据追溯与实验复现。 2. 数据 pipeline 研发：开发多模态数据清洗、去重、质量打分及合成数据 pipeline，基于 Ray、Spark 等框架优化 CPU/GPU 混合任务的调度、吞吐与容错，支持大规模数据生产。 3. 湖仓与引擎研发：参与湖仓存储与查询引擎研发，深入列式存储、索引、查询执行与 I/O 优化，提升海量数据的扫描、过滤和检索效率，优化与 dataloader 的对接。 4. 后训练算法平台研发：围绕 SFT、偏好优化与 RL，开发训练、rollout、评测等任务的编排与运行管理，完善实验配置、模型与 Checkpoint 管理、监控和故障恢复，提升实验效率。 5. 算法工具链研发：和算法团队一起开发可复用的 rollout、reward 与评测组件，以及 SDK、CLI 和调试工具，支持算法组件接入、样本追踪、实验对比与 bad case 回流，加快新方法的实现与验证。 6. 评测 Infra 研发：开发评测集、指标与任务管理，优化分布式推理和结果汇总，支持多模型、多版本的自动化评测与回归，建设结果对比和 bad case 分析工具，支撑数据及后训练迭代。

我们期待你 1. 计算机、软件工程或相关专业在校生，数据结构、算法与计算机基础扎实，熟练掌握 Python、Go、Java、C++ 中至少一种语言。 2. 熟悉 Linux，在数据库、分布式系统、后端开发或机器学习工程中的至少一个方向有项目实践。 3. 能阅读源码、定位问题，通过实验分析性能或稳定性，讲清楚自己的设计、实现与验证结果。 4. 对大模型数据和后训练 Infra 有兴趣，能主动学习，和算法、系统同学协作推进研发。 加分项 • 有 Ray、Spark、Flink 或工作流引擎实践，处理过任务调度、数据倾斜、容错或性能问题。 • 接触过 Iceberg、Lance、Arrow/Parquet，或有列式存储、索引、查询引擎相关研究与开发经验。 • 有 PyTorch、verl 等框架实践，参与过 SFT/RL 训练、rollout、reward 或评测模块开发。 • 有算法平台、SDK、CLI、实验管理、调试工具或评测框架开发经验，或相关开源贡献。 你将收获 参与数据准备、后训练与模型评测的完整流程，做出算法团队日常使用的平台与工具。

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