Staff Site Reliability Engineer, Compute
Crusoe(1 month ago)
About this role
The Staff Site Reliability Engineer, Compute at Crusoe is responsible for deploying and optimizing sustainable, AI-first cloud infrastructure, focusing on virtualization, hypervisor, and kernel-level performance. This role involves developing automation and observability tools, managing the virtualization stack using technologies like KVM and QEMU, and collaborating with hardware teams to troubleshoot performance bottlenecks and optimize workloads for modern AI and HPC demands. The engineer will also be engaged in kernel tuning, system-level debugging, and integrating enhancements for guest VM reliability.
Required Skills
- Compute Infrastructure
- Site Reliability Engineering
- Linux Kernel Internals
- Virtualization Technologies
- KVM
- QEMU
- SmartNICs
- High-Throughput Networking
- System-Level Debugging
- Infrastructure as Code
+6 more
Qualifications
- 8+ years of professional experience in Compute SRE, Linux system engineering, or compute infrastructure roles
- Strong proficiency in Linux kernel internals
- Experience with virtualization architectures and technologies such as KVM, Xen, QEMU, or VMware
- Familiarity with SmartNICs/DPUs (e.g., NVIDIA CX6/7, BlueField-3)
- Expert-level skills in at least one programming language: Go, C or Rust
- Experience with system-level debugging, including kdump, kexec, and kernel panic analysis
- Proficiency in Infrastructure as Code tooling and CI/CD practices for bare-metal or cloud infrastructure
- Strong understanding of compute scheduling, resource management, and high-throughput networking
About Crusoe
crusoe.aiCrusoe is a leading provider of next-generation AI infrastructure that focuses on renewable-powered cloud computing solutions. By employing an energy-first approach, Crusoe enables businesses to deploy AI workloads at scale while ensuring reliable performance and round-the-clock support. The company is committed to advancing sustainable technology, making it a strategic partner for organizations looking to enhance their AI capabilities in an environmentally conscious manner.
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