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Open nowPosted 45 days ago

具身智能MLOps平台工程师

agirobot/referral515 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now具身智能MLOps平台工程师agirobot/referral · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. agirobot/referral postings stay open a median of 1 days.

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 45 days ago

agirobot/referral median: 1 days open

The posting

职位概述 负责智元具身智能MLOps平台研发，建设训练任务、实验管理、流水线及模型注册能力，支持数据挂载、Checkpoint管理与故障恢复，为算法团队提供可追踪、可复现的模型研发环境。 主要职责 1. 建设训练任务管理能力，支持环境配置、提交、状态查询、日志查看、重试与终止，对接计算团队提供的资源队列和调度服务。 2. 接入PyTorch及分布式训练框架，提供单机多卡、多机多卡训练模板和启动机制，沉淀环境验证与常见故障诊断能力。 3. 建设MLflow类实验管理能力，记录代码版本、运行环境、参数、指标和训练产物，支持实验查询、对比与结果追溯。 4. 对接数据与存储服务，管理数据版本关联和挂载配置，与算法团队约定Checkpoint接口，完善保留策略与任务恢复流程。 5. 建设训练Pipeline和模型注册能力，接入算法团队的训练与评估程序，编排数据准备、训练、评估和产物登记流程。 6. 协同算法与基础设施团队定位任务启动、通信、数据读取及恢复异常，完善平台API、自动化测试、使用文档和训练基准。 承担主要目标/关键任务 1. 建设训练任务管理能力，支持环境配置、提交、状态查询、日志查看、重试与终止，对接计算团队提供的资源队列和调度服务。 2. 接入PyTorch及分布式训练框架，提供单机多卡、多机多卡训练模板和启动机制，沉淀环境验证与常见故障诊断能力。 3. 建设MLflow类实验管理能力，记录代码版本、运行环境、参数、指标和训练产物，支持实验查询、对比与结果追溯。 4. 对接数据与存储服务，管理数据版本关联和挂载配置，与算法团队约定Checkpoint接口，完善保留策略与任务恢复流程。 5. 建设训练Pipeline和模型注册能力，接入算法团队的训练与评估程序，编排数据准备、训练、评估和产物登记流程。 6. 协同算法与基础设施团队定位任务启动、通信、数据读取及恢复异常，完善平台API、自动化测试、使用文档和训练基准。

任职要求 1. 教育背景：本科及以上学历，计算机、人工智能、软件工程、自动化、机器人等相关专业优先。 2. 工作经验：3年以上机器学习平台、训练基础设施或后端研发经验，参与过训练平台或分布式训练工程交付；具有5年以上相关经验及核心模块设计经验者优先。 3. 熟练掌握Python，具备服务端开发、API设计及数据存储基础，能够独立完成平台模块开发、测试和问题定位。 4. 熟悉Linux、容器和Kubernetes作业机制，理解训练任务与资源队列的关系，能够对接底层调度和存储服务。 5. 熟悉PyTorch训练流程，了解分布式训练启动、数据加载、模型保存和恢复，能够分析常见训练环境与运行问题。 6. 在任务编排、实验追踪、Checkpoint或模型版本管理中至少一个领域有实践，能将算法研发流程转化为平台功能。 加分项 1. 有MLflow、Kubeflow或同类平台二次开发经验，熟悉训练流水线和模型产物管理。 2. 有具身智能、多模态或强化学习训练工程实践，或具备主流分布式训练框架接入与排障经验。

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