Remote AI Performance Engineer - GPU & ML Systems

Bright Vision Technologies; Farmington Hills (MI); On-site; USD 75,000 - 100,000; Full time

Benefits offered by this job

Remote work

Job summary

Bright Vision Technologies is seeking an AI Performance Engineer for a fully remote role in the United States. The position focuses on maximizing throughput, reducing latency, and lowering costs across training and inference workloads for large neural networks.

The ideal candidate has 6+ years of experience in performance engineering or ML systems, with strong Python and C++ skills, plus hands-on GPU optimization and distributed training expertise.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a 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 grasp of memory hierarchies, communication primitives, and parallelism strategies.
• Excellent measurement, debugging, and analytical reasoning skills.
• Strong communication and collaboration skills.

Responsibilities

• Focus on throughput, latency, and cost optimization across training and inference workloads.
• Tuning from kernel level to distributed systems with profiler instrumentation.
• Collaborate with product, design, and engineering teams; mentor junior engineers.

Skills

Python

C++

GPU optimization

Distributed ML

Profiling tools

Model compression

Memory hierarchy

Measurement & debugging

Communication & collaboration

Education

Bachelor’s or Master’s degree in CS/CE or related field

Tools

Profiling tools

Triton/CUTLASS

TensorRT/DeepSpeed

Job description

Bright Vision Technologies is seeking an AI Performance Engineer for a fully remote role in the United States. The position focuses on maximizing throughput, reducing latency, and lowering costs across training and inference workloads for large neural networks.

The ideal candidate has 6+ years of experience in performance engineering or ML systems, with strong Python and C++ skills, plus hands-on GPU optimization and distributed training expertise.