Member of Technical Staff (AI Platform) - AI Infrastructure

Keen to join a company that champions growth and development? Join one of the most exciting AI infrastructure companies in the market, building a platform that deploys and operates large-scale GPU clusters for some of the world's leading AI labs. Working with tens of thousands of GPUs across a global network of data centres, the organisation delivers the infrastructure powering next-generation AI training and inference at scale.

This role offers the opportunity to work on complex, production-scale AI infrastructure without the layers of bureaucracy often found in larger organisations. You'll have the freedom to shape how the platform evolves while solving engineering challenges that have a direct impact on customers. Ready to make a move? Get in touch and apply today! Responsibilities: You will be building and operating the automated systems that take a cluster from bare machines to customer-ready, end to end You will be managing machine lifecycle between tenants: join, wipe, verify, rejoin, reliably and at scale You will be operating Kubernetes and Postgres across the fleet, keeping critical infrastructure healthy under real production load You will be contributing to custom Kubernetes operators that power the control plane You will be scaling clusters from tens of nodes to thousands, solving the problems that only show up at the edges of scale You will be participating in on-call rotations and responding to production incidents with the depth of knowledge to resolve them quickly Skills / Must Have: A track record of impressive technical work you can speak to in depth, the years matter less than the quality of the work and its real-world impact 2+ years of on-call experience for critical production services Deep Kubernetes experience, not just consuming it but understanding what is happening underneath Strong Linux fundamentals across kernel, cgroups, containers, networking, and storage Experience operating databases, monitoring, CI/CD, and cloud infrastructure at scale Familiarity with fleet management and capacity planning Desirable Skills: Experience writing Kubernetes operators Background in GPU infrastructure, HPC scheduling, or bare-metal hardware Benefits: Meaningful equity Fully remote across North America Full insurance coverage for you and your dependants Salary: $250,000 to $300,000 base salary