USAMember of the Technical Staff - Systems
1 мес. назад
USALeadRemote
rustclinuxvirtualizationcontainer runtimesperformance engineering
Engineer focusing on designing and building high-performance systems including storage, networking, virtualization, and container runtimes for AI infrastructure.
Обязанности
- We are looking for strong engineers with experience and interest in designing and building high performance systems across, but not limited to: storage, networking, virtualization, container runtimes.
Требования
- Impressive technical work you can go deep on, with impact in the world. That can take three years or twenty.
- Experience building high-performance distributed systems at scale
- Strong low-level Linux foundations: kernel, drivers, filesystems, containers, PCIe
- Experience with performance engineering
- Production experience in Rust, C, or Go
- Ability to participate in on-call rotations and respond to production incidents
- Experience with QEMU/KVM, eBPF, RDMA, or BIOS/UEFI internals is nice to have, but not required.
- Cluster is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Другое
- Location: North America Remote / San Francisco, CA · Full-Time
- Compute is the most sought-after resource in the world, yet it still trades like commercial real estate: year-long contracts, manual fulfillment, capacity sitting idle because nobody can move it. We are building the liquidity layer at .
- was founded by Nat Friedman and Daniel Gross to give startups the scaled AI infrastructure once reserved for hyperscalers. The first cluster filled almost instantly. The years since went into the platform that makes compute liquid: it deploys into foreign datacenters and turns the hardware it finds into clusters that leading AI labs train on.
- Today operates compute for 80+ customers across 30+ capacity providers, with tens of thousands of GPUs under management and billions of GPU-hours supported, on everything from A100 to GB300.