Remote AI Infrastructure Engineer for ML Platform

Visa Hunt; United States; On-site; 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 powering 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.

The ideal candidate has built or operated production AI infrastructure at scale,

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 6+ years of infrastructure, platform, or HPC engineering experience.
• Hands-on experience operating GPU clusters or large-scale ML training infra.
• Proficiency in Python and at least one systems language (Go or C++).
• Understanding of distributed training, accelerators, and collective communication.
• Experience with Kubernetes, Slurm, Ray, or similar ML schedulers.
• Strong Linux internals, networking, and high-performance storage knowledge.
• Experience with at least one major cloud ML infra offering.
• Strong software engineering practices: testing, CI/CD, code review.
• Excellent communication and cross-functional collaboration.

Skills

Python

Go

C++

Kubernetes

Slurm

Ray

Linux

CI/CD

Distributed training

Networking

Open-source

Education

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

Tools

InfiniBand networking

RDMA networking

CI/CD pipelines

Git

Job description

Bright Vision Technologies is seeking an Intelligent Infrastructure Engineer to design, build, and operate the platform layer powering 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.

The ideal candidate has built or operated production AI infrastructure at scale,