AI Performance Engineer for Scale-Out AI Clusters

Cornelis Networks, Inc.; San Jose (CA); Remote; USD 140,000 - 200,000; Full time

Job summary

Cornelis Networks, Inc. is seeking an AI Performance Engineer to optimize training and multi-node inference across our scale-out networking platforms.

You will collaborate with architecture, firmware, software, and lighthouse customers to translate lab results into field-proven wins. Responsibilities include measuring and boosting performance for distributed AI workloads, benchmarking across frameworks, and tuning CPU/GPU pipelines and interconnects.

Qualifications

• Bachelor’s degree in CS/EE/CE/Math or related; MS preferred.

Responsibilities

• Measure & optimize end-to-end performance for distributed AI workloads (training + multi-node inference) on CPU/GPU clusters and various fabrics.

Skills

AI benchmarks

Distributed training

PyTorch

DeepSpeed

NCCL/RCCL

Linux performance tuning

C/Python scripting

Education

BS in CS/EE/CE/Math or related

Tools

Nsight Systems

VTune

perf

Prometheus/Grafana

GCC/LLVM/OneAPI

Job description

Cornelis Networks, Inc. is seeking an AI Performance Engineer to optimize training and multi-node inference across our scale-out networking platforms.

You will collaborate with architecture, firmware, software, and lighthouse customers to translate lab results into field-proven wins. Responsibilities include measuring and boosting performance for distributed AI workloads, benchmarking across frameworks, and tuning CPU/GPU pipelines and interconnects.