Remote AI Systems Performance Architect

Bright Vision Technologies; Oregon; Hybrid; USD 130,000 - 180,000; Full time

Job summary

Bright Vision Technologies is seeking a highly experienced AI Systems Performance Specialist with 10+ years of experience in AI infrastructure, machine learning systems, High-Performance Computing (HPC), and performance engineering. The ideal candidate will optimize AI training and inference workloads for maximum performance, scalability, reliability, and cost efficiency.

This role requires deep expertise in GPU optimization, distributed training, Large Language Model (LLM) inference, Python,

Qualifications

• 10+ years of professional experience in performance engineering or AI infrastructure.
• Deep expertise in GPU-accelerated workloads, CUDA, distributed training and modern DL libraries.
• Expert-level programming in Python and C++.
• Experience profiling with Nsight, PyTorch Profiler, TensorBoard or similar tools.
• Experience deploying AI workloads on AWS/Azure/GCP.

Responsibilities

• Optimize AI training and inference pipelines for maximum throughput and low latency.
• Improve GPU utilization, memory management and multi-GPU performance across production workloads.
• Apply optimization techniques including quantization, pruning, mixed precision, batching and model parallelism.
• Profile applications and identify bottlenecks across compute, memory, networking, and storage.
• Lead performance optimization initiatives and mentor engineering teams.

Skills

Python

C++

GPU optimization

Distributed computing

Performance engineering

Education

Bachelor’s or Master’s degree in a related technical discipline

Tools

CUDA

NCCL

DeepSpeed

PyTorch

TensorRT

Job description

Bright Vision Technologies is seeking a highly experienced AI Systems Performance Specialist with 10+ years of experience in AI infrastructure, machine learning systems, High-Performance Computing (HPC), and performance engineering. The ideal candidate will optimize AI training and inference workloads for maximum performance, scalability, reliability, and cost efficiency.

This role requires deep expertise in GPU optimization, distributed training, Large Language Model (LLM) inference, Python,