Remote ML Infrastructure Engineer — GPU Clusters & AI Platform

United States Digital Space LLC; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

BV Teck seeks an AI Infrastructure Engineer to design, build, and operate the platform powering large‑scale AI training and inference workloads. You will focus on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers, with emphasis on reliability and cost efficiency.

The role requires hands‑on experience with production AI infrastructure at scale, understanding hardware, kernel, scheduler, and ML frameworks, and strong software

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Six 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 setups.
• Build scheduling, queuing, and resource-sharing systems to maximize accelerator utilization.
• Integrate PyTorch, JAX, DeepSpeed, Megatron-LM, and Ray Train into a unified platform.
• Operate high-performance storage systems and data pipelines for fast data access.
• Design networking architectures with RDMA, InfiniBand, NCCL, and high-bandwidth communication.
• Develop observability for AI workloads including utilization and failure analytics.
• Implement checkpointing, restart, and fault-tolerance for long-running training jobs.
• Drive cost optimization across compute, storage, and networking via scheduling and spot capacity.
• Develop tooling and workflows to empower researchers to launch experiments safely.
• Plan capacity with research teams for upcoming training runs.
• Implement security controls and multi-tenant access management.
• Automate cluster provisioning, lifecycle management, and config enforcement.
• Maintain runbooks and capacity dashboards for the AI platform.

Skills

Python

Systems programming (Go/C++)

Distributed training

CI/CD

Linux internals

Communication

Education

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

Six+ years of infrastructure/engineering experience

Tools

Kubernetes

Slurm

Ray

NCCL

Job description

BV Teck seeks an AI Infrastructure Engineer to design, build, and operate the platform powering large‑scale AI training and inference workloads. You will focus on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers, with emphasis on reliability and cost efficiency.

The role requires hands‑on experience with production AI infrastructure at scale, understanding hardware, kernel, scheduler, and ML frameworks, and strong software