Remote AI Systems Performance Engineer

Bright Vision Technologies; Orlando (FL); A distancia; USD 100.000 - 150.000; Jornada completa

Descripción de la vacante

Bright Vision Technologies is seeking an AI Performance Optimization Engineer to maximize throughput, minimize latency, and reduce cost for AI training and inference workloads on a remote-capable stack.

The role requires 6+ years in performance engineering or ML systems, strong Python and C++, experience with GPU optimization and distributed training, and proficiency with profiling tools. You will collaborate with cross-functional teams to deliver production-ready optimizations.

Formación

• Bachelor's or master's degree in computer science, computer engineering, or related field.
• Six or more years of experience in performance engineering, ML systems, or HPC.
• Strong proficiency in Python and C++.
• Hands-on experience optimizing deep learning workloads on modern GPUs.

Responsabilidades

• Optimize AI workloads across CPU/GPU and distributed systems.
• Profile, measure, and optimize throughput and latency.
• Collaborate with product, design, engineering, operations, and business stakeholders.

Conocimientos

Python

C++

Performance engineering

Distributed training/inference

GPU optimization

Profiling & instrumentation

Memory hierarchy

Debugging & analytics

Communication & collaboration

Educación

Bachelors degree in CS/CE or related field

Masters degree in CS/CE or related field

Herramientas

TensorRT

Triton

CUTLASS

DeepSpeed

Profiling tools (Nsight, perf)

Descripción del empleo

Bright Vision Technologies is seeking an AI Performance Optimization Engineer to maximize throughput, minimize latency, and reduce cost for AI training and inference workloads on a remote-capable stack.

The role requires 6+ years in performance engineering or ML systems, strong Python and C++, experience with GPU optimization and distributed training, and proficiency with profiling tools. You will collaborate with cross-functional teams to deliver production-ready optimizations.