Infrastructure Engineer (GPU & Compute)

Lightning AI•San Francisco, NY

5d•Hybrid

About The Position

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team. In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software—developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads. You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one. We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

Requirements

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/programming languages for automation
Ability to debug complex issues across hardware, OS, GPUs, and system software

Nice To Haves

Experience with high-performance interconnects (e.g., InfiniBand, 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

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 OS 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, OS, 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 (e.g., IPMI, 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