Remote AI Performance Engineer — GPU & ML Systems

Bright Vision Technologies; United States; Remote; USD 75,000 - 100,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Performance Engineer to maximize throughput, minimize latency, and cut costs across training and inference for large neural networks. The role spans from low-level kernel optimization to distributed system tuning, with deep knowledge of GPU architecture, memory management, and compiler-level optimization.

You will collaborate with product, design, engineering, and operations to translate ambiguous requirements into robust solutions, raise the bar

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• Six+ 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

• Maximize throughput and minimize latency across training and inference workloads.
• Optimize GPU kernels and distributed system components.
• Collaborate with cross-functional teams to translate requirements into robust solutions.
• Mentor junior engineers and participate in code/design reviews.
• Deliver production-grade AI performance improvements with measurable impact.

Skills

Python

C++

GPU optimization

Profiling tools

Distributed training

Measurement & debugging

Education

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

Tools

Triton

CUTLASS

TensorRT

DeepSpeed

Job description

Bright Vision Technologies is seeking an AI Performance Engineer to maximize throughput, minimize latency, and cut costs across training and inference for large neural networks. The role spans from low-level kernel optimization to distributed system tuning, with deep knowledge of GPU architecture, memory management, and compiler-level optimization.

You will collaborate with product, design, engineering, and operations to translate ambiguous requirements into robust solutions, raise the bar