Senior AI Platform Engineer - Remote

Bright Vision Technologies; Edison (NJ); Remote; 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, scheduling, storage performance, and developer experience for ML engineers and researchers.

The ideal candidate has built or operated production AI infrastructure at scale, understands hardware, kernel, scheduler, and ML framework interactions, and brings 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 across on-prem, cloud, and hybrid environments.
• Build scheduling, queueing, and resource-sharing systems to maximize accelerator utilization across teams.
• Integrate PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform.
• Operate high-performance storage systems and data pipelines feeding training data at near-line rate.
• Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth communication.
• Develop 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 tooling and paved-road workflows for researchers to launch experiments safely.
• Plan capacity with research and applied ML teams for upcoming training rounds.
• Implement security controls, isolation, and multi-tenant access management.
• Automate cluster provisioning, lifecycle management, and configuration enforcement.
• Maintain runbooks, dashboards, and operational docs for the AI platform.

Skills

Python

Go

C++

Linux

Distributed training

Education

Bachelor’s or Master’s in CS or related

Tools

Kubernetes

Slurm

Ray

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, scheduling, storage performance, and developer experience for ML engineers and researchers.

The ideal candidate has built or operated production AI infrastructure at scale, understands hardware, kernel, scheduler, and ML framework interactions, and brings strong software engineering