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Open nowPosted 879 days ago

大模型编排调度工程师（训练&推理方向）

vrfi1sk8a0/index201 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now大模型编排调度工程师（训练&推理方向）vrfi1sk8a0/index · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. vrfi1sk8a0/index postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  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 879 days ago

vrfi1sk8a0/index median: 1 days open

The posting

1. 平台与基础设施建设： 负责 MiniMax 大模型训练与推理平台的开发，设计并实现 LLM 相关的工程架构与工具链，保障基建稳定性，支撑公司大模型业务的高速迭代与部署效率。 2. 大规模 GPU 资源调度： 负责超大规模、多云多集群、异构 GPU 资源的管理、编排与调度；集成多种训推资源管理体系和框架进行统一管理，向全局最优逼近，提升资源流转效率和 GPU 综合利用率。 3. LLM 训推编排抽象： 深入业务场景，对 LLM 训练与推理服务完成编排抽象，持续迭代并落地高效的部署模式。 4. 弹性伸缩与效率流转： 负责服务以及集群的弹性伸缩能力建设；与流量调度、任务调度层深度协作，在保障大模型训推服务质量（SLA）的前提下，完成复杂场景下高效的资源流转与在离线混部。

1. 基础素质： 计算机及相关专业，本科及以上学历；扎实的计算机体系结构、数据结构与算法、分布式系统基础。 2. 编程与架构能力： 熟练掌握 Golang / Python / C++ 中至少一种，具备优秀的工程素养和代码品味；深入理解常规架构设计思想（服务化、异步、高可用、可扩展等）。 3. 云原生与调度底盘： 熟悉 Kubernetes 及云原生技术栈，深入理解 kube-scheduler、volcano、koordinator 等至少一种调度解决方案。 4. LLM 架构经验（加分）： 熟悉大语言模型（LLM）生态，对 MoE、PD 分离（Prefill-Decode 分离）、EP 并行（专家并行）等大模型前沿架构有实际工程经验者优先。 5. 复杂场景经验（加分）： 具有大规模异构集群维护、多云多集群架构、大规模弹性系统、大规模训练任务和推理服务的编排、在离线混部及资源调度经验者优先。 6. 极客精神与软素质： - 具备良好的团队沟通合作能力、责任心、自驱力和快速学习能力； - 有 ACM/ICPC、OI 等算法竞赛获奖经历者优先； - 对 AI 充满热情，善于使用 AI Coding 工具，有通过 AI Agent 提升工程链路和架构迭代效率经验者优先。

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