Senior Systems Performance Engineer
Core
Develop and tune synthetic GPU workloads and AI training/inference frameworks to stress hardware subsystems, analyze performance anomalies, and build automation for validation coverage.
Role type
Senior IC systems performance engineer (GPU/accelerated computing)
Builds
Automated test plans, performance models, and validation coverage for GPU accelerated computing products
Domain
Hardware/Software systems engineering, GPU architecture, AI infrastructure
Deliverable
production ML models
Required skills
GPU architecture analysis, performance modeling, CUDA programming, Python, Linux debugging, AI workload profiling, system telemetry analysis, automated test design
Preferred skills
NVIDIA Dynamo, TensorRT-LLM, vLLM, SGLang, CUDA kernel optimization, x86/Arm server familiarity, NVLink/PCIe/InfiniBand knowledge, hardware error/thermal telemetry analysis
Technologies
CUDA, PyTorch, TensorRT-LLM, vLLM, SGLang, Linux, Python, NCCL, cuBLAS, CUTLASS
Responsibilities
Develop synthetic GPU workloads to stress hardware subsystems; onboard and adapt AI training/inference workloads to new GPU platforms; design controlled experiments correlating model predictions with telemetry; analyze performance anomalies and hardware/software failures; build automation for workload deployment and telemetry collection
Seniority
Senior, hands-on IC
