Top Engineering Jobs in Seattle, WA

As a Principal Engineer at CoreWeave, you will design cluster orchestration systems, lead technical direction, ensure system reliability, and mentor engineers while focusing on large-scale GPU cluster performance for AI workloads.

As a Senior Software Engineer in Cluster Orchestration, you'll lead multiple services, drive improvements in performance and reliability, and mentor junior engineers.

Lead operational readiness reviews for large-scale data center projects, identify design/construction/commissioning gaps, drive corrective actions, validate turnover readiness, coordinate across design, construction, commissioning, and operations to ensure mission-critical infrastructure meets standards and is handed off reliably.

The Senior Software Engineer will enhance Kubernetes-native benchmarking services while improving performance and reliability, mentoring junior engineers throughout the process.

As a Staff Engineer, you'll lead the orchestration platform strategy, mentor engineers, and ensure reliable workloads across GPU clusters, directly impacting AI innovation.

Responsibilities include designing, developing, and maintaining automated tooling for Linux systems, collaborating with teams, and ensuring software delivery.

Build, maintain, and optimize scalable front-end systems and web experiences. Translate Figma designs into reusable components, support large-scale site migrations, improve performance, accessibility, and SEO, and work with cross-functional teams using modern workflows and AI-assisted tools.

Debug and fix complex kernel and container runtime interactions for a large GPU fleet: investigate kernel crashes, cgroup and namespace edge cases, and scheduler/memory issues; develop and upstream kernel or container-runtime patches; build observability tooling and partner with hardware, platform, and fleet teams during incident response.

Own and evolve a Kubernetes-native test framework that qualifies host images on real hardware. Build test harnesses, extend coverage into HPC, Slurm-on-Kubernetes and firmware/hardware, keep CI fast and reliable at fleet scale, and own results, reporting, and triage. Collaborate with kernel, firmware, imaging, and HPC teams and explore LLM-driven log triage and failure classification.

Design and build Linux-based execution environments for GPU workloads, extending virtualization and runtime technologies. Debug and optimize Linux kernel, hypervisor, GPU drivers, and container runtimes. Develop observability tooling, improve performance and isolation, and collaborate across security, platform, and networking teams to support multi-tenant AI infrastructure.