Remote AI Infrastructure Engineer: GPU Clusters & ML Platform

Bright Vision Technologies; Port Reading (NJ); Teletrabalho; USD 100 000 - 160 000; Tempo integral

Resumo da oferta

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. Focus areas include GPU clusters, scheduling, storage performance, and developer experience for ML engineers and researchers.

The role emphasizes reliability, efficiency, and cost control, requiring hands-on production infra experience and deep software engineering discipline across hardware, kernel, scheduler, and ML

Qualificações

• Bachelor’s or Master’s degree in Computer Science or related field.
• 10+ years of experience in 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 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.]
• Job responsibilities include designing and operating GPU/accelerator infrastructure for training/inference across on-prem, cloud, and hybrid setups; building scheduling/queueing systems; integrating frameworks like PyTorch, JAX, DeepSpeed, and Ray Train; ensuring high-performance storage and data pipelines; designing RDMA/InfiniBand networking; building observability and fault-tolerance; driving cost optimization; enabling researchers with robust tooling; planning capacity with ML teams; enforcing security and automation; maintaining runbooks and capacity dashboards; staying current with AI infra research.

Responsabilidades

• 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, FSDP, Megatron-LM, and Ray Train into a unified platform.
• Operate high-performance storage systems and data pipelines with near-line-rate data feeding.
• Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth communication.
• Build observability for AI workloads including utilization and training stability.
• Implement checkpointing, restart, and fault-tolerance for long-running training jobs.
• Drive cost optimization across compute, storage, and networking.
• Develop developer tooling and paved-road workflows for researchers.
• Partner with research and applied ML teams to plan capacity for training runs.
• Implement security controls and multi-tenant access management.
• Automate cluster provisioning and lifecycle management.
• Maintain runbooks and capacity dashboards for the AI platform.
• Stay current with AI infra research and open-source tooling.

Conhecimentos

Python

Go or C++

Kubernetes

Slurm

Ray

CI/CD

Linux

Networking

CI/CD

Formação académica

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

Ferramentas

NCCL

InfiniBand

Descrição da oferta de emprego

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. Focus areas include GPU clusters, scheduling, storage performance, and developer experience for ML engineers and researchers.

The role emphasizes reliability, efficiency, and cost control, requiring hands-on production infra experience and deep software engineering discipline across hardware, kernel, scheduler, and ML