CoreWeave

Build secure, high-performance sandboxed runtime environments for GPU-accelerated Kubernetes workloads in multi-tenant cloud infrastructure. You’ll work across container runtimes, lightweight virtualization, Linux systems, GPU scheduling, and performance optimization.

Build and operate CoreWeave’s high-performance, multi-tenant file and block storage services for large-scale AI workloads. This senior systems role spans storage data paths, Kubernetes delivery, control-plane capabilities, and production reliability.

Serve as the named technical partner for existing AI customers, helping them adopt CoreWeave, solve production challenges, and expand their AI workloads. This hands-on solutions architecture role combines customer relationship ownership with deep expertise in LLM applications, cloud infrastructure, and AI platforms.

Principal Software Engineer leading the frontend architecture, performance, and reliability of the W&B Models application. This role combines hands-on React development with broad architectural influence across engineering teams.

Lead the architecture of globally distributed, security-critical systems powering CoreWeave’s authorization, authentication, and security infrastructure. This principal-level individual contributor role combines deep distributed-systems design with cross-team technical leadership and mentorship.

Build and own full-stack applications for CoreWeave’s internal infrastructure operations, from user interface through data model and production operations. The role combines modern web development with AI-native features such as natural-language interfaces, agents, and evaluation systems.

Build and ship full-stack software for CoreWeave’s internal data infrastructure, including UNION, operational applications, and AI-facing interfaces. You’ll work with TypeScript, React, Next.js, Python, Kubernetes, SQL, and governed data to deliver features directly to internal users.

Lead the design and delivery of production machine learning systems that turn large-scale infrastructure telemetry into actionable insights for troubleshooting, optimization, and reliability. This staff-level role combines ML engineering, evaluation, data services, and production systems leadership.