Staff Software Engineer, Applied Training

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com .

What You’ll Do:

A lab signs with CoreWeave. They have thousands of GPUs waiting. Their first month? Spent on cluster setup instead of research. Building deployment scripts, fighting container images, wiring up job orchestration. They came to train models. Instead, they're doing operations.

This is the problem. We're building the Applied Training team to fix it.

You'll be an early member of a small team, responsible for our Kubernetes-native research cluster platform, or the sandbox client for agentic training and evaluation, or possibly a new project altogether. The goal is specific: Give every CoreWeave customer the research infrastructure that currently only exists inside frontier labs.

About the role:

• Contribute to the roadmap for Applied Training. Figure out what actually unlocks new workloads and what's just nice to have. Work directly and closely with customers, and other teams inside of CoreWeave that are building cloud native primitives. Compute, storage, networking, etc.
• For the research cluster platform: design and build a complete research cluster experience. CLI, job configuration schema, Kubernetes operators, daemons. Solve the problems researchers actually hit: code distribution, checkpoint-triggered evaluation, cross-cluster scheduling, programmatic job control. Replace the patchwork of scripts customers keep building on their own.
• For sandbox infrastructure: own the Python SDK and work in a very tight loop with the backend team. When an RL training run needs to spawn thousands of isolated containers for agent rollouts, that's this system. When someone wants to run agent benchmarks at scale, that's this system. Make it work with our Kubernetes clusters, storage, and auth so researchers don't have to think about infrastructure.
• Write the documentation for running popular OSS training frameworks on CoreWeave. The work that can unblock customers and help them succeed.
• Work with infrastructure teams and customers directly. The customers are large AI labs running thousands of GPUs. Understand how they structure their internal supercomputing stacks. Bring that knowledge back to what we build.

Who You Are:

• 8-12+ years building distributed systems, ML infrastructure, or developer platforms.
• Real Kubernetes experience: custom controllers, operators, scheduling, CR