Senior AI Infrastructure Engineer - Remote & Scaled GPU

Bright Vision Technologies; Nashua (NH); On-site; USD 100,000 - 160,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Infrastructure 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 strong emphasis on reliability, efficiency, and cost control.

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

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• 10+ 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.

Responsibilities

• Design and operate GPU and accelerator infrastructure for training and inference across on-prem, cloud, and hybrid configurations.
• Build scheduling, queueing, and resource-sharing systems to maximize accelerator utilization.
• Integrate PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform.
• Operate high-performance storage systems and data pipelines for near-line-rate data feeds.
• Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth IPC.
• Develop observability for AI workloads including utilization, throughput, and fault analytics.
• Implement checkpointing, restart, and fault-tolerance for long-running training jobs.
• Drive cost optimization through scheduling, spot capacity, and right-sizing.
• Develop developer tooling and paved-road workflows for researchers.

Skills

Python

Go

C++

Distributed systems

Linux

CI/CD

Kubernetes

Ray

Networking

Education

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

Tools

Kubernetes

Slurm

Ray

PyTorch

DeepSpeed

Job description

Bright Vision Technologies is seeking an AI Infrastructure 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 strong emphasis on reliability, efficiency, and cost control.

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