Principal Software Engineer (Models)

• You will own the frontend architecture of the W&B app, the product ML researchers and engineers work in every day, and be accountable for app performance, stability and reliability
• A single page in W&B assembles data from many parts of the product, which power different product features owned by different teams
• Individually those requests are all reasonable; in aggregate they contribute to increased load times and a worse experience for users
• Performance here is a question of composition: what queries each page needs before it can render, what queries can add to that set, and how those boundaries hold as the product grows
• You’ll define those boundaries and make the calls they depend on
• This role is frontend-led but architecture-deep and organizationally wide
• You’ll spend time shaping other teams’ designs and building consensus across boundaries, and you’ll own execution of your own plans when that’s what it takes to land them
• In this role you’ll be responsible for the architecture, performance, and stability of the W&B Models frontend, defining the frontier of innovation for the team, and managing cross team requirements within the Models system
• Some examples of what you’ll do:
• Setting performance targets and driving the work that meets them, with results proven in production data
• Deciding the app’s delivery and rendering architecture, including how code is delivered efficiently
• Partnering with backend and platform teams on API design, including moving work out of the client
• Proposing and driving the larger overhauls that incremental work cannot reach
• Investing in our people is one of our top priorities, and we value candidates who can bring their diversified experiences to our teams
• Here are some qualities we’ve found compatible with our team
• We’d love to talk about whether this aligns with your experience and interests and what you’re excited to work on next

Have led the transformation of a large, long-lived React application with a focus on performance, product impact and dev experience and owned the outcomeHands-on experience with bundlers and build tooling, and clear views on code splitting and delivery tradeoffsEnough backend depth to design systems at a high level. You can propose a new API architecture in service of a faster client and reason about its frontend implicationsTrack record of validating ideas, coordinating across engineering teams, and sequencing work that spans organizational boundariesAn operator mindset: you measure, you ship, you follow through, and you stay close to productionSolid client-side caching fundamentals, including normalization, invalidation, and the failure modes that appear at scaleStrong command of React and TypeScript, with production experience in GraphQL and a modern state management approach such as Redux or Zustand, including opinions on when each is the right toolReal performance engineering skill: you can instrument an application, read both frontend and backend traces, determine precisely where time is going, and prove the improvement with numbers8+ years building user-facing software, with deep expertise in frontend architecture and performanceThis position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing processExperience introducing automated enforcement such as lint rules, CI gates, or performance budgets that changed engineering behavior broadlyBackground in data-dense or visualization-heavy applications where rendering cost and data volume are the core constraintsFamiliarity with observability tooling such as Datadog RUM and APM, or comparable tracing and session-replay stacksWorking knowledge of Go or a similar backend languageExposure to ML, MLOps, or AI agent workflows, or genuine curiosity about the researchers and engineers who use these toolsExperience with a highly configurable product, where the space of user and deployment settings can’t be exhaustively tested

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