AI Systems Performance Engineer - Remote

Bright Vision Technologies; Tampa (FL); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is hiring an AI Infrastructure Engineer to optimize AI workloads across training and inference pipelines. This 100% remote US role requires deep GPU, kernel, and distributed systems expertise to drive performance and cost efficiency.

You will partner with product, design, and operations to translate requirements into scalable, measurable improvements and mentor peers to raise engineering quality across projects.

Qualifications

• 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.
• Deep understanding of distributed training and inference techniques.
• Experience with profiling tools across CPU, GPU, and distributed systems.
• Familiarity with model compression techniques and their accuracy implications.
• Strong memory hierarchy knowledge and parallelism strategies.
• Excellent measurement, debugging, and analytical reasoning skills.
• Strong communication and collaboration skills.

Responsibilities

• Extract maximum throughput and minimize latency across training and inference workloads.
• Tune full-stack from kernel optimization to distributed system performance.
• Collaborate with product, design, engineering, operations, and business stakeholders.
• Mentor junior engineers and participate in code/design reviews.

Skills

Python

C++

Performance engineering

GPU optimization

Distributed training

Profiling tools

Model compression

Memory hierarchies

Debugging & analytics

Communication skills

Education

Bachelor's or Master's degree in CS/CE

Tools

Triton

CUTLASS

TensorRT-LLM

DeepSpeed

vLLM

Job description

Bright Vision Technologies is hiring an AI Infrastructure Engineer to optimize AI workloads across training and inference pipelines. This 100% remote US role requires deep GPU, kernel, and distributed systems expertise to drive performance and cost efficiency.

You will partner with product, design, and operations to translate requirements into scalable, measurable improvements and mentor peers to raise engineering quality across projects.