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Intelligent Infrastructure Engineer

Bright Vision Technologies•United States•🌍 Remote
Full-timeSenior
$100K - $150K
per year
👁️ 0 views•📝 0 applications•Posted 10/14/2026•Expires 12/13/2026
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Job Description

Intelligent Infrastructure Engineer – Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: Intelligent Infrastructure Engineer Location: 100% Remote (United States) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 Annually Experience: 6+ years Sponsorship: U. S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply.

We are unable to sponsor new H-1B visa petitions for this position.

Job Summary

We are 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.

The ideal candidate has built or operated production AI infrastructure at scale, understands the interaction between hardware, kernel, scheduler, and ML framework, and brings strong software engineering discipline to platform work.

Required 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 p

Required Skills

C++KubernetesLinuxMachine LearningPythonSoftware Engineering

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