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Lightning AI

Cloud-based AI development and deployment platform

Infrastructure Engineer - GPU & Compute

Platform EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of experience in infrastructure engineering, systems engineering, or related roles.
  • Strong Linux systems experience in production environments.
  • Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM.
  • Familiarity with bare-metal provisioning and system bring-up workflows.
  • Proficiency in Python or similar scripting or programming languages for automation.
  • Ability to debug complex issues across hardware, operating systems, GPUs, and system software.

Responsibilities

  • Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure.
  • Run and maintain test clusters used for system validation, diagnostics, and bring-up.
  • Validate firmware, drivers, and operating system images across compute and GPU-enabled systems.
  • Support hardware qualification efforts for next-generation platforms.
  • Own GPU diagnostics and validation workflows across large-scale infrastructure.
  • Diagnose and resolve complex issues across GPUs, drivers, operating systems, and hardware layers.
  • Analyze system and GPU performance using tools such as NVIDIA DCGM.
  • Identify failure patterns and drive improvements in system stability and validation coverage.
  • Build and maintain automation for provisioning, validation, and system bring-up.
  • Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead.
  • Improve the reliability, repeatability, and scalability of image pipelines and validation systems.
  • Manage and operate Linux-based systems in production and validation environments.
  • Manage virtualization technology.
  • Support bare-metal provisioning workflows, including PXE and image-based systems.
  • Interface with hardware management systems such as IPMI and Redfish for monitoring and debugging.
  • Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation.
  • Collaborate with platform and ML teams to ensure systems meet workload requirements.
  • Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure.

Desired Qualifications

  • Experience with high-performance interconnects such as InfiniBand and NVLink.
  • Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows.
  • Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish.
  • Data center operations experience, including working with physical hardware.
  • Experience supporting AI/ML or HPC workloads at scale.
  • Experience with GPU validation frameworks or large-scale hardware qualification processes.

About the Company

Lightning AI

Cloud-based AI development and deployment platform

Lightning AI builds a cloud-based platform for AI development that covers the full lifecycle from ideation to deployment. It provides a browser-based environment called AI Studio, a virtual laptop with persistent storage and configurable environments, enabling users to code on CPUs, debug on GPUs, and scale to multi-node deployments without local setup. The platform supports tools like PyTorch Lightning, Fabric, Lit-GPT, and torchmetrics to help data scientists and developers prototype, train on GPUs, and optimize models. Pricing is subscription-based, targeting enterprises and individual developers who need robust, scalable AI development capabilities. The goal is to streamline AI creation and deployment by simplifying access to compute, tooling, and scalable infrastructure in one cloud-based workspace.

Company size
201-500
Company stage
Late Stage VC
Total funding
$108.6M
Headquarters
New York City, New York
Founded
2015

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