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Open nowPosted 9 hours ago

AI infra研发工程师（具身）

agirobot/referral529 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen nowAI infra研发工程师（具身）agirobot/referral · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. agirobot/referral postings stay open a median of 5 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted 9 hours ago

agirobot/referral median: 5 days open

The posting

负责支撑人形机器人数据、仿真、训练、评测四条流水线的工程系统,让算法团队从"能跑通"走到"能稳定迭代、能量产"，以下方向四选一，具体如下：

方向一：数据管线与平台 1、建设遥操作与真机采集的数据链路:VR、动捕、外骨骼采集端到多相机、关节状态、力触觉的同步对齐、清洗、质量打分。 2、大规模数据存储与检索:LeRobot、RLDS、HDF5等格式的写入与转换,视频编码与切片，数据版本、血缘与权限。 3、训练侧数据供给:高吞吐并行解码、采样权重、数据配比实验，定位并解决 I/O 瓶颈。 方向二：仿真系统 1、基于 Isaac Lab、Isaac Sim、MuJoCo、Genesis之一，搭建万级并行环境的训练与评测仿真。 2、场景与资产生成、域随机化、传感器仿真(深度、触觉、IMU)，缩小 sim2real gap。 3、物理参数辨识与真机对标，建立"仿真结果可信"的验收标准。 方向三：训练框架 1、分布式训练基础设施:FSDP、DeepSpeed、Megatron 等方案的落地与调优，覆盖 VLA与大规模强化学习两类负载。 2、异构资源调度:Kubernetes、Slurm、Ray，GPU 利用率与排队时延的可观测与优化。 3、实验管理:配置版本、checkpoint、失败恢复、指标看板，让一次训练可复现。 方向四：评测系统 1、建立统一的评测口径:任务集、指标(成功率、鲁棒性、泛化、时延)、评分脚本。 2、仿真批量评测与真机自动化评测台架，支持多机型、多版本并行跑。 3、模型发布门禁与回归测试:每次迭代自动出报告，异常自动归因到数据、模型或环境。

1、计算机、自动化、机器人或相关专业，硕士及以上，3年以上相关经验； 2、Python 熟练，C++ 能读能改，熟悉 Linux 与容器化部署； 3、有大规模系统的实战经验:处理过 TB级数据、千卡级训练、或万级并发任务中的至少一类； 4、能读懂算法侧的论文和代码，把需求翻译成系统设计，而不是等接口文档； 5、对机器人有基本理解:关节、坐标系、控制频率、真机与仿真的差异；

加分项 - 在具身智能、自动驾驶、大模型任一领域做过 Infra，有从零搭到生产可用的经历。 - 熟悉 Isaac Sim、ManiSkill、RoboSuite 等仿真平台，或参与过开源具身项目。 - 有 GPU 性能优化经验:CUDA、Triton、NCCL 通信、显存与吞吐调优。 - 熟悉数据质量体系:标注、审核、难例挖掘、数据飞轮。

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