Intelligent Infrastructure Engineer

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 for large-scale AI workloads. You’ll focus on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, emphasizing reliability and cost efficiency.

The ideal candidate has built or operated production AI infrastructure at scale, understands hardware–kernel–scheduler–ML framework

Qualifications

• Bachelor’s or Master’s degree in CS or a related field.
• 6+ years of experience in infrastructure, platform, or HPC engineering.
• Hands-on experience operating GPU clusters or large-scale ML training infra.
• Strong Python and at least one systems language such as Go or C++.
• Deep understanding of distributed training and accelerator architectures.
• Experience with Kubernetes, Slurm, Ray for ML workloads.
• Strong Linux internals, networking, and high-performance storage.
• Experience with major cloud ML infrastructure offerings.
• Strong software engineering practices including testing, CI/CD, and code review.
• Excellent communication and cross-functional collaboration skills.

Skills

Python

Distributed training

Linux internals

Networking

CI/CD practices

Communication skills

Cross-functional collaboration

Education

Bachelor's or Master's degree in CS or related field

Tools

Go

C++

Kubernetes

Slurm

Ray

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 CardHolders, EADHolders, 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 provider’s ML infrastructure offerings.
• Strong software engineering practices including testing, CI/CD, and code review.
• Excellent communication and cross-functional collaboration skills.

Preferred Qualifications

• Experience operating InfiniBand or RDMA networking at scale.
• Contributions to open-source ML infrastructure projects.
• Familiarity with custom orchestrators or research-grade training stacks.
• Exposure to frontier model training operations.
• Experience with FinOps for AI workloads.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.