Software / AI Infrastructure Engineer (GPU Clusters)

Location: Remote within the United States or Canada

Base salary up to $250,000 USD plus bonus and RSUs.

Company

Cloud technology company developing AI infrastructure and GPU cloud computing solutions for organizations building and scaling AI and ML systems.

What you will do

• Design and develop Python backend services and automation tooling for a large-scale GPU-cluster fleet.
• Build provisioning, testing, and lifecycle management systems for physical hardware, including bare-metal software.
• Integrate Linux systems, shell scripting, low-level tooling, and CI/CD pipelines for infrastructure software.
• Work across IPv4/IPv6, DHCP, DNS, network boot, and hardware management controllers and protocols.
• Design NoSQL data stores for system state and orchestration.
• Support ARM64 architectures and contribute documentation and operational excellence across large machine fleets.

Requirements

• Strong Python engineering experience with a solid Linux and shell scripting background.
• Hands-on familiarity with bare-metal servers, networking fundamentals, and hardware management interfaces and APIs.
• Experience with CI/CD pipelines and NoSQL databases.
• Ability to debug complex issues spanning software, hardware, and networks.
• Strong ownership mindset and clear communication skills in a distributed team.

Nice to have

• Experience at large infrastructure scale, with ARM platforms in production, or in hardware testing and factory provisioning.
• Background in infrastructure automation, internal platform tooling, or open-source systems software.

Culture & Benefits

• Flat structure with minimal bureaucracy and a focus on ownership, speed, and technical excellence.
• Hands-on work with NVIDIA hardware and direct collaboration with customers and internal teams.
• Remote work within the United States or Canada.
• Base salary up to $250,000 USD plus bonus and RSUs.
• No take-home assignment during the hiring process.

Hiring process

• Preliminary interview.
• Technical coding interview.
• Final technical deep dive.