Software Engineer

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.

About the Role:

Reporting to the Senior Engineering Manager for ML Workflows, this Senior Software Engineer will own the architecture and evolution of core systems in the Weights & Biases platform.

ML Workflows owns what customers use to move models and data through W&B. Artifacts is the versioned data layer that every object logged to W&B runs through. Registry sits on top of it as the organization-wide source of truth for what is production-ready, and it is used by teams at Pinterest, Dropbox, and Canva. Automations is the event and action layer the rest of the platform builds on. Launch is execution infrastructure that runs customer ML and agent workloads.

You will own systems end to end, from design through production reliability, working across the W&B backend, the Python SDK, and the frontend. You will partner closely with product managers, designers, and ML platform engineers, and you will talk directly to enterprise ML teams about their workflows. We hire senior engineers into the organization and match them to a team based on their strengths and interests, which we discuss with you during the interview process.

W&B is part of CoreWeave, so these products are being built onto CoreWeave infrastructure, and there is real room to shape how that happens.

What You'll Do

• Own the architecture and evolution of a core platform area, designing systems that scale to billions of artifacts and high-volume event and job throughput.
• Dive deep into system architecture to find optimization opportunities, solve complex bugs, and make the difficult calls that balance short-term delivery against long-term platform health.
• Work across the stack as the problem requires, from Go backend services and GraphQL APIs to the Python SDK and the TypeScript frontend.
• Lead migrations and re-architecture of systems carrying live customer traffic, keeping the experience seamless for the customers who depend on them.
• Identify and refactor technical debt, improving maintainability and developer productivity.
• Establish engineering patterns and best practices that hold up as the platform grows.