Remote AI Infrastructure Engineer: GPU & ML Platform

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

Job summary

Bright Vision Technologies is seeking an Intelligent Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads.

The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with strong emphasis on reliability, efficiency, and cost control.

Qualifications

• Degree in Computer Science or related field.
• 6+ years of infrastructure, platform, or HPC engineering.
• Hands-on experience operating GPU clusters or ML training infra.
• Proficiency in Python and Go or C++.
• Understanding of distributed training and accelerator architectures.
• Experience with Kubernetes, Slurm, Ray, or similar ML schedulers.
• Strong Linux internals, networking, and high-performance storage.
• Experience with at least one major cloud provider’s ML infra.
• Strong software engineering practices: testing, CI/CD, code reviews.
• Excellent communication and collaboration skills.

Responsibilities

• Design, build, and operate the platform layer for AI workloads.
• Focus on GPU clusters, distributed training, scheduling, and storage performance.
• Improve developer experience for ML engineers and researchers.

Skills

Python programming

Systems programming

Distributed training

Communication

Cross-functional collaboration

Education

Bachelor’s or Master’s degree in Computer Science or a related field

Tools

Kubernetes

Slurm

Ray

Go

C++

Linux

Job description

Bright Vision Technologies is seeking an Intelligent Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads.

The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with strong emphasis on reliability, efficiency, and cost control.