huaweicanada · Vancouver, British Columbia, Canada
Huawei Canada has an immediate permanent opening for a Senior Engineer. About the team: The Computing Data Application Acceleration Lab aims to create a leading global data analytics platform organized into three specialized teams using innovative programming technologies. This team focuses on full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers. This team also develops next-generation GPU architecture for gaming, cloud rendering, VR/AR, and Metaverse applications. One of the goals of this lab are to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness. About the job: As a Senior System Engineer, you will drive core compute operator development and distributed scaling performance across foundation model pre-training and post-training workloads on Ascend NPUs. You will identify computational and communication bottlenecks, implement high-performance kernels using AscendC, Triton, and TileLang, and optimize distributed acceleration suites (MindSpeed / open-source training frameworks). Ascend High-Performance Kernel Development: Design, implement, and tune core operators (FlashAttention variants, FP8/MXFP8/W4A8 GEMM, Fused RMSNorm, dynamic MoE routing/dispatch) using AscendC, with explorations in Triton (Triton-Ascend backend) and TileLang. Pre-training & Post-training System Optimization: Architect, scale, and optimize distributed pre-training and RL post-training pipelines using MindSpeed (MindSpeed-LLM / MindSpeed-MM) alongside upstream frameworks (Megatron-LM / Megatron-Core, PyTorch FSDP, veRL, vLLM, Ray). Distributed Parallelism & Training Efficiency: Tune multi-dimensional hybrid parallelism (TP, PP, CP, EP, ZeRO/FSDP) and RL rollout/actor pipelining on Ascend NPU clusters, achieving optimal MFU and compute-communication overlap. Low-Precision & Numerical Parity: Implement low-precision training/inference schemes (FP8, MXFP8, mixe…
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