Senior AI Infra Engineer - Remote & GPU Scale

Bright Vision Technologies; East Brunswick Township (NJ); Remote; USD 100,000 - 160,000; Full time

Job summary

Bright Vision Technologies is hiring an AI Infrastructure Engineer to design, build, and operate platform layers powering large-scale AI training workloads. You will focus on GPU clusters, distributed training, scheduling, storage, and developer tooling for ML researchers, ensuring reliability, efficiency, and cost control.

The role requires hands-on experience with GPU infrastructure, Kubernetes or Slurm, and deep knowledge of ML frameworks integration, with strong software engineering

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Ten 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 and operate GPU and accelerator infrastructure for training and inference, spanning on-prem clusters, cloud-managed services, and hybrid configurations.
• Build scheduling, queueing, and resource-sharing systems that maximize accelerator utilization across many teams.
• Integrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform offering.
• Operate high-performance storage systems and data pipelines that keep accelerators fed with training data at near-line-rate.
• Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth collective communication.
• Build observability for AI workloads including utilization, throughput, training stability, and failure-mode analytics.
• Implement checkpointing, restart, and fault-tolerance patterns for long-running training jobs at scale.
• Drive cost optimization across compute, storage, and networking through scheduling, spot capacity, and right-sizing.
• Develop developer tooling and paved-road workflows that let researchers launch experiments safely and efficiently.
• Partner with research and applied ML teams to plan capacity for upcoming training runs.
• Implement security controls, isolation, and access management for multi-tenant AI infrastructure.
• Drive automation across cluster provisioning, lifecycle management, and configuration enforcement.
• Maintain runbooks, capacity dashboards, and operational documentation for the AI platform.
• Stay current with AI infrastructure research, accelerator hardware, and emerging open-source AI tooling.

Skills

Python

Go or C++

Kubernetes

Slurm

Ray

Pytorch

DeepSpeed

Megatron-LM

Education

Bachelor’s or Master’s in CS

Tools

NCCL

Job description

Bright Vision Technologies is hiring an AI Infrastructure Engineer to design, build, and operate platform layers powering large-scale AI training workloads. You will focus on GPU clusters, distributed training, scheduling, storage, and developer tooling for ML researchers, ensuring reliability, efficiency, and cost control.

The role requires hands-on experience with GPU infrastructure, Kubernetes or Slurm, and deep knowledge of ML frameworks integration, with strong software engineering