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Open nowPosted 227 days ago

AI Infrastructure Lead

agirobot/referral515 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen nowAI Infrastructure Leadagirobot/referral · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% 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. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 227 days ago

agirobot/referral median: 1 days open

The posting

职位背景 我们正在建设一个面向 具身智能（Embodied AI）与机器人学习 的大规模研究中心，拥有 大规模 GPU 集群与真实机器人数据闭环。团队致力于研发 多模态大模型（Multimodal Foundation Model）、VLA（Vision-Language-Action）、强化学习（Reinforcement Learning）与世界模型（World Model） 等核心技术。

我们在招聘 ML Infrastructure Lead，负责设计和建设支持大规模模型训练的 机器学习平台与分布式训练基础设施，包括 训练系统、GPU 集群调度、实验平台与数据训练 pipeline，以支持研究团队在大规模计算环境下高效进行模型训练与算法迭代。

工作职责

负责机器学习基础设施与训练平台的架构设计与建设 设计并维护 大规模 GPU 集群训练系统（H100/H200 等） 构建支持 大模型（LLM / Multimodal / VLA） 的分布式训练系统 搭建 训练 pipeline（dataset → preprocessing → training → evaluation → deployment） 设计和实现 实验管理系统（Experiment Tracking）、模型版本管理（Model Registry） 优化 GPU 利用率、通信效率与训练稳定性 与研究团队合作支持 大模型训练、强化学习训练与多模态模型训练 与机器人系统团队合作，实现模型 推理部署（Inference / Serving） 组建并领导 ML Infrastructure 团队

任职要求

计算机、人工智能或相关专业 硕士及以上学历 5年以上机器学习工程或 AI 平台经验 熟悉主流深度学习框架：PyTorch / JAX / TensorFlow 熟悉分布式训练技术：FSDP / Megatron / DeepSpeed / Horovod 熟悉 GPU 集群与训练调度系统：Slurm / Kubernetes / Ray 熟悉机器学习训练 pipeline 与数据系统：dataset pipeline / experiment tracking / model registry 熟悉 GPU 计算优化：CUDA / NCCL / mixed precision / memory optimization 具备良好的系统架构能力与团队协作能力 加分项

有大模型训练（LLM / Multimodal Foundation Model） 经验 有强化学习（RL / RLHF / Offline RL） 训练平台经验 有自动驾驶 ML Infra 或 AI 平台团队经验 有管理 数百至上千 GPU 集群训练任务 的经验 有构建 AI Training Platform / ML Platform 的经验

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