Lightning AI is the company behind PyTorch Lightning, building an end-to-end platform for developing AI systems. They are seeking a GPU & Compute Infrastructure Engineer to manage image systems and validation across large-scale compute infrastructure, focusing on GPU-enabled systems and automation for AI/ML workloads.

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

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
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

Lightning AI

Open Positions (2)

Engineering

Research Engineer

Infrastructure Engineer (GPU & Compute)

Hiring Team