Senior AI Infrastructure Engineer — Remote

Bright Vision Technologies; Framingham (MA); 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 that powers large-scale AI training and inference workloads. The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with emphasis on reliability and cost control.

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

Qualifications

• Bachelor’s or Master’s degree in CS or related field.
• 10+ years in infrastructure, platform, or HPC engineering.
• Hands-on experience operating GPU clusters or large-scale ML training infra.
• Proficiency in Python and at least one systems language (Go or C++).
• Understanding of distributed training, accelerators, and collective communication.
• Experience with Kubernetes, Slurm, Ray for ML workloads.
• Strong Linux internals, networking, and high-performance storage.
• Experience with cloud ML infra offerings.
• Strong software engineering practices including testing, CI/CD, and code review.
• Excellent communication and cross-functional collaboration.

Responsibilities

• Design and operate GPU and accelerator infra for training and inference.
• Build scheduling, queueing, and resource sharing to maximize utilization.
• Integrate PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform.
• Operate high-performance storage and data pipelines for near-line-rate training data.
• Design networking architectures supporting RDMA, InfiniBand, NCCL.
• Develop observability for AI workloads including throughput and failure analytics.
• Implement checkpointing, restart, and fault-tolerance for long-running training jobs.
• Drive cost optimization across compute, storage, and networking.
• Develop tooling and paved-road workflows for researchers to run experiments safely.
• Plan capacity with research and applied ML teams for upcoming runs.
• Implement security controls and multi-tenant isolation.
• Automate cluster provisioning, lifecycle management, and configuration enforcement.
• Maintain runbooks, capacity dashboards, and operational documentation.
• Stay current with AI infra research, accelerator hardware, and open-source tooling.

Skills

Python

Go or C++

Linux internals

Distributed training

GPU clusters

CI/CD

Communication

Education

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

Tools

Kubernetes

Slurm

Ray

PyTorch

DeepSpeed

NCCL

Megatron-LM

FSDP

InfiniBand

Job description

Bright Vision Technologies is seeking an AI Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads. The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with emphasis on reliability and cost control.

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