Ai基础架构工程师-大规模集群方向
Tasks
- Build Kubernetes based AI training platform
- Ensure high availability and capacity planning
- Implement checkpointing for training resumption
- Integrate deep learning frameworks for efficient cluster execution
- Maintain Linux drivers CUDA and cuDNN
- Maintain NCCL communication libraries
- Manage GPU cluster operations
- Monitor GPU RDMA network and storage end to end
- Optimize dataloader performance
- Optimize distributed training startup workflow
- Optimize scheduler for resource isolation and priority scheduling
- Optimize training performance in software and hardware layers
- Troubleshoot distributed training failures
Perks/Benefits
- N/A
Skills/Tech-stack
Automation tools | CUDA | CUDNN | Ceph | Containerd | DCGM | DDP | DeepSpeed | Docker | FSDP | GPFS | Golang | Golang Automation Tools | Grafana | Infiniband | Kubeflow | Kubernetes | Kubernetes Operator | Language model training | Large Language Model | Large language model training | Linux | Lustre | Megatron | Megatron-LM | Minio | Model Training | NCCL | NVIDIA A100 | NVIDIA GPU | NVIDIA H100 | NVLink | NVSwitch | Pipeline parallelism | Prometheus | PyTorch | Python | RDMA | RoCE | TensorFlow | Volcano
Education
Roles
AI | AI Infrastructure Engineer | Engineer | Infrastructure Engineer | Platform | Platform Engineer
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