Senior AI Infrastructure Engineer - Remote

Bright Vision Technologies; United States; Remote; USD 100,000 - 160,000; Full time

Job summary

Bright Vision Technologies in the United States is seeking an AI Infrastructure Engineer to design, build, and operate the platform layer powering large-scale AI workloads. You will focus on GPU clusters, scheduling, storage, and developer experience for ML engineers and researchers.

The role emphasizes reliability, cost control, and interaction between hardware, kernel, scheduler, and ML frameworks, with strong software engineering discipline.

Qualifications

• Bachelor’s or Master’s in CS or a related field.
• 10+ years of infrastructure, platform, or HPC engineering.
• Hands-on experience operating GPU clusters or large-scale ML training infrastructure.
• Proficiency in Python and at least one systems language (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 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 frameworks such as PyTorch, JAX, DeepSpeed, and Ray Train into a unified platform.
• Operate high-performance storage systems and data pipelines for near-line-rate data access.
• Design networking architectures with RDMA, InfiniBand, NCCL, and high-bandwidth communication.
• Build observability for AI workloads including utilization, throughput, and failure analytics.
• Implement checkpointing, restart, and fault-tolerance patterns for long-running training jobs.
• Drive cost optimization across compute, storage, and networking via scheduling and right-sizing.
• Develop developer tooling and paved-road workflows for safe, efficient experiment launches.
• Plan capacity with research and applied ML teams for upcoming training runs.

Skills

Python

Go

C++

Distributed training

Kubernetes

Slurm

Ray

Linux

CI/CD

Communication

Education

Bachelor’s or Master’s in CS

Tools

PyTorch

JAX

DeepSpeed

Megatron-LM

Ray Train

GPU clusters tooling

Job description

Bright Vision Technologies in the United States is seeking an AI Infrastructure Engineer to design, build, and operate the platform layer powering large-scale AI workloads. You will focus on GPU clusters, scheduling, storage, and developer experience for ML engineers and researchers.

The role emphasizes reliability, cost control, and interaction between hardware, kernel, scheduler, and ML frameworks, with strong software engineering discipline.