Senior AI Systems Engineer — Remote GPU ML Infra

Bright Vision Technologies; Yuba City (CA); Remote; USD 90,000 - 100,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Systems Engineer to design, build, and operate the platform layer powering large-scale AI training and inference workloads. The role emphasizes GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with a strong focus on reliability, efficiency, and cost control.

The ideal candidate has 6+ years of infrastructure or HPC experience, deep Python and systems language

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Six or more years of experience in infrastructure, platform, or HPC engineering.
• Hands-on experience operating GPU clusters or large-scale ML training infrastructure.
• Strong proficiency in Python and at least one systems language such as Go or C++.
• Deep understanding of distributed training, accelerator architectures, and collective communication.
• Experience with Kubernetes, Slurm, Ray, or similar scheduling systems for ML workloads.
• Strong understanding of Linux internals, networking, and high-performance storage.
• Experience with at least one major cloud provider’s ML infrastructure 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 training and inference workloads.
• Focus on GPU clusters, distributed training frameworks, scheduling, and storage performance.
• Improve reliability, efficiency, and cost control for ML infrastructure.

Skills

Python

Go or C++

Kubernetes

Slurm

Ray

Distributed training

CI/CD

Linux internals

Education

Bachelor's or Master's in Computer Science

Tools

Kubernetes

Slurm

Ray

InfiniBand

Job description

Bright Vision Technologies is seeking an AI Systems Engineer to design, build, and operate the platform layer powering large-scale AI training and inference workloads. The role emphasizes GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with a strong focus on reliability, efficiency, and cost control.

The ideal candidate has 6+ years of infrastructure or HPC experience, deep Python and systems language