大模型训练系统专家
Tasks
- Build LLM experiment and training platform
- Build distributed training stability and fault recovery system
- Build end to end training performance analysis and bottleneck detection
- Design high performance checkpoint and training state management
- Ensure checkpoint consistency and cross topology recovery
- Implement fault detection diagnosis and root cause analysis
- Improve GPU utilization and training throughput
- Isolate faults and automate retry and checkpoint restore
- Manage training artifacts and model evaluations
- Manage training data and experiment configurations
- Monitor training metrics and observability
- Optimize distributed checkpoint throughput and write read performance
- Orchestrate training tasks and pipelines
- Track experiments and enable experiment reproducibility
Perks/Benefits
- N/A
Skills/Tech-stack
C++ | Cause analysis | Checkpointing | Cloud Native | Computer Architecture | Consistency | Data loading | DeepSpeed | Distributed Storage | Distributed Systems | Distributed Training | Docker | FSDP | Fault Diagnosis | GPU Computing | Go | High Performance | High performance IO | Infiniband | Kubernetes | MegatronLM | NVLink | Observability | Operating Systems | PyTorch | Python | RDMA | Ray | RoCE | Root Cause Analysis | Root cause | Rust
Education
N/A
Regions
Countries
States
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