Senior AI Infrastructure Engineer - Remote GPU Clusters

Bright Vision Technologies; United States; 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 emphasizes GPU clusters, scheduling, storage performance, and developer experience for ML engineers and researchers, with an emphasis on reliability and cost control.

The ideal candidate has 6+ years in infrastructure or HPC, expert Python and a systems language (Go or C++), and hands-on GPU infra plus

Qualifications

• Six or more years in infrastructure, platform, or HPC engineering.
• Hands-on experience operating GPU clusters or large-scale ML training infra.
• Proficiency in Python and a systems language (Go or C++).
• Experience with Kubernetes, Slurm, Ray, or similar ML schedulers.
• Strong understanding of Linux internals, networking, and high-performance storage.
• Experience with at least one major cloud provider’s ML infra offerings.
• Strong software engineering practices including testing, CI/CD, and code review.
• Excellent communication and cross-functional collaboration skills.

Responsibilities

• Design, build, and operate the platform layer powering large-scale AI workloads.
• Improve reliability, efficiency, and cost control for GPU-based training.
• Collaborate with ML engineers and researchers across teams.
• Bridge software engineering with hardware and kernel interactions.

Skills

Python

Go or C++

GPU clusters

Distributed training

Kubernetes

Slurm

Ray

Linux internals

Cloud ML infra

CI/CD

Code review

Communication

Education

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

Tools

InfiniBand

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 emphasizes GPU clusters, scheduling, storage performance, and developer experience for ML engineers and researchers, with an emphasis on reliability and cost control.

The ideal candidate has 6+ years in infrastructure or HPC, expert Python and a systems language (Go or C++), and hands-on GPU infra plus