Senior Distributed LLM Performance Engineer
Huawei Canada
Distributed LLM performance engineering powers Huawei Canada’s Ascend NPU training systems with MindSpeed, hybrid parallelism, and profiling expertise.
This Senior System Engineer position focuses on foundation-model pre-training and post-training at scale. You will architect distributed pipelines using MindSpeed, Megatron, PyTorch FSDP, veRL, vLLM, and Ray. The work targets MFU, compute-communication overlap, rollout pipelining, and reliable numerical behavior.
Key Responsibilities:
- Scale pre-training and RL post-training pipelines across NPU clusters
- Optimize hybrid TP, PP, CP, EP, and ZeRO parallelism
- Tune RL rollout and actor pipelining for training efficiency
- Implement FP8, MXFP8, and mixed-precision training schemes
- Eliminate pipeline bubbles, stalls, and HCCL communication overhead
Requirements:
- Three-plus years in HPC, accelerator operators, or distributed training
- Practical distributed training experience with listed frameworks
- Proficiency in C/C++ and modern Python systems programming
- Hands-on PyTorch custom C++ or CANN extension development
- Performance profiling experience on AI hardware
Build scalable Ascend NPU training systems by combining distributed frameworks, parallelism tuning, profiling, and precision alignment.
#J-18808-LjbffrReference: WJ-2742_586336 · Posted 14 Nov 2026, 12:17 AM