Remote Senior AI Systems Performance Engineer

Bright Vision Technologies; Fishers (IN, KY); Remote; USD 130,000 - 180,000; Full time

Job summary

Bright Vision Technologies is seeking an experienced AI Systems Performance Specialist to optimize AI training and inference workloads across enterprise-scale platforms. You will lead GPU optimization, multi-GPU training, and production AI system enhancements, with a strong focus on CUDA, Python, and C++.

The role requires 10+ years in AI infrastructure, HPC, or performance engineering, plus hands-on expertise with distributed frameworks and cloud deployments (AWS/Azure/GCP).

Qualifications

• 10+ years of professional experience in performance engineering.
• Experience with GPU-accelerated AI workloads and HPC.
• Proficiency in Python and C++.
• Experience deploying AI workloads on AWS/Azure/GCP.
• Strong leadership and communication skills.

Responsibilities

• Optimize AI training and inference pipelines for throughput, latency, and scale.
• Analyze and improve GPU utilization, memory, and multi-GPU performance.
• Implement optimization techniques (quantization, pruning, mixed precision, batching).
• Profile AI apps with industry tools and identify bottlenecks across compute, memory, networking, storage.
• Coordinate with researchers, ML engineers, and infra teams to improve production AI performance.
• Build benchmarking frameworks, performance dashboards, and regression tests.
• Evaluate new AI hardware and frameworks to improve enterprise AI capabilities.
• Drive AI infrastructure cost optimization and FinOps best practices.
• Mentor teams on AI systems architecture and GPU optimization.

Skills

Python

C++

Performance engineering

GPU optimization

Education

Bachelor's or Master's in CS/CE/EE/AI

Tools

CUDA

NCCL

DeepSpeed

Triton Inference Server

FasterTransformer

vLLM

TensorRT-LLM

MPI

Job description

Bright Vision Technologies is seeking an experienced AI Systems Performance Specialist to optimize AI training and inference workloads across enterprise-scale platforms. You will lead GPU optimization, multi-GPU training, and production AI system enhancements, with a strong focus on CUDA, Python, and C++.

The role requires 10+ years in AI infrastructure, HPC, or performance engineering, plus hands-on expertise with distributed frameworks and cloud deployments (AWS/Azure/GCP).