Remote ML Infrastructure Engineer - GPU & Scale

Bright Vision Technologies; United States; Remote; USD 100,000 - 150,000; 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. You will focus on GPU clusters, distributed training, scheduling, and data pipelines for ML engineers and researchers.

The role emphasizes reliability, efficiency, and cost control, with emphasis on GPU hardware interaction, kernel, and ML framework collaboration. Remote US-based candidates are welcome.

Qualifications

• Six+ years of infrastructure or HPC engineering experience.
• Hands-on experience operating GPU clusters or large-scale ML training infrastructure.
• Proficiency in Python and systems languages (Go or C++).
• Experience with Kubernetes, Slurm, Ray, or similar ML scheduling.
• Strong Linux, networking, and high-performance storage knowledge.
• Experience with at least one major cloud provider’s ML infra offerings.
• Strong CI/CD, testing, and code review practices.
• Excellent communication and cross-functional collaboration skills.

Responsibilities

• Design and operate GPU and accelerator infrastructure for training and inference, spanning on-prem, cloud, and hybrid setups.
• Build scheduling, queueing, and resource-sharing systems to maximize accelerator utilization.
• Integrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform.
• Operate high-performance storage systems and data pipelines to feed training data at near-line rate.
• Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth communications.
• Build observability for AI workloads including utilization, throughput, and failure analytics.
• Implement checkpointing and fault-tolerance patterns for long-running training jobs.
• Drive cost optimization across compute, storage, and networking via scheduling and spot capacity.
• Develop developer tooling and workflows for researchers to launch experiments safely.
• Collaborate with research and applied ML teams to plan capacity for upcoming runs.
• Implement security controls, isolation, and access management for multi-tenant infra.
• Automate cluster provisioning, lifecycle management, and configuration enforcement; maintain runbooks and dashboards.
• Stay current with AI infra research, accelerator hardware, and open-source tooling.
• Experience with FinOps for AI workloads.

Skills

Python

Go

C++

Linux

Education

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

Tools

PyTorch

JAX

DeepSpeed

FSDP

Megatron-LM

Ray Train

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. You will focus on GPU clusters, distributed training, scheduling, and data pipelines for ML engineers and researchers.

The role emphasizes reliability, efficiency, and cost control, with emphasis on GPU hardware interaction, kernel, and ML framework collaboration. Remote US-based candidates are welcome.