Staff Software Engineer, Performance- Weights & Biases

Coreweave; United States; À distance; USD 180 000 - 270 000; Plein temps

Résumé du poste

CoreWeave, the essential cloud for AI, is seeking a Staff Engineer for Performance Engineering on the Weights Biases integration. You will own complex performance challenges across the WB platform and infrastructure, pushing the boundaries of scalability and latency.

In this role, you will design experiments, build benchmarking and load-testing frameworks, and drive initiatives to prevent regressions across surfaces, empowering teams to deliver fast, reliable experiences for AI workloads.

Qualifications

• Proven experience leading performance engineering efforts.
• Strong background in benchmarking, load testing, and latency optimization.
• Ability to translate performance data into actionable improvements.

Responsabilités

• Take technical ownership of complex performance challenges across the WB platform and infrastructure.
• Design and lead experiments to improve system scalability and latency.
• Develop standardized benchmarking and load-testing frameworks.
• Drive initiatives to prevent regressions across product surfaces.

Connaissances

Performance engineering

System benchmarking

Load testing

Description du poste

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.

Weights Biases at CoreWeave

CoreWeave acquired Weights Biases to create the most powerful end-to-end platform to develop, deploy, and iterate AI faster.

CoreWeave operates a growing footprint of data centers covering every region of the US and across Europe, and was ranked as one of the TIME100 most influential companies of 2024.

By bringing together CoreWeave's industry-leading cloud infrastructure with the best-in-class tools AI practitioners know and love from Weights Biases, we're setting a new standard for how AI is built, trained, and scaled.

The integration of our teams and technologies is accelerating our shared mission: to empower developers with the tools and infrastructure they need to push the boundaries of what AI can do. From experiment tracking and model optimization to high-performance training clusters, agent building, and inference at scale, we're combining forces to serve the full AI lifecycle - all in one seamless platform.

Weights Biases has long been trusted by over 1,500 organizations - including AstraZeneca, Canva, Cohere, OpenAI, Meta, Snowflake, Square, Toyota, and Wayve - to build better models, AI agents and applications. Now, as part of CoreWeave, that impact is amplified across a broader ecosystem of AI innovators, researchers, and enterprises.

As we unite under one vision, we're looking for bold thinkers and agile builders who are excited to shape the future of AI alongside us. If you're passionate about solving complex problems at the intersection of software, hardware, and AI, there's never been a more exciting time to join our team.

What You'll Do:

Performance Engineering at Weights Biases ensures our systems and products scale seamlessly as usage grows. We embed performance thinking into every stage of development-diagnosing issues, designing scalable patterns, and building tools that empower every engineering team to deliver fast, efficient, and reliable experiences. Our mission is to make performance a shared responsibility across the company through data, automation, and collaboration.

About the role:

As a Staff Engineer on the Performance Engineering team, you'll take technical ownership of complex performance challenges across the W B platform and infrastructure. You'll design and lead experiments to improve system scalability and latency, develop standardized benchmarking and load testing frameworks, and drive initiatives to prevent regressions across product surfaces. Yo