Software Engineer, Sweeps - Weights & Biases

Weights and Biases
Livingston, NJ / New York, NY / San Fransisco, CA / Sunnyvale, CA / Bellevue, WA$109k – $160kPosted 1 March 2026

Job Description

<div class="content-intro"><div id="message-list_1758129707.765969" class="c-virtual_list__item" data-qa="virtual-list-item" data-item-key="1758129707.765969"> <div class="c-message_kit__background c-message_kit__background--hovered p-message_pane_message__message c-message_kit__message" data-qa="message_container" data-qa-unprocessed="false" data-qa-placeholder="false"> <div class="c-message_kit__hover c-message_kit__hover--hovered" data-qa-hover="true"> <div class="c-message_kit__actions c-message_kit__actions--default"> <div class="c-message_kit__gutter"> <div class="c-message_kit__gutter__right" data-qa="message_content"> <div class="c-message_kit__blocks c-message_kit__blocks--rich_text"> <div class="c-message__message_blocks c-message__message_blocks--rich_text" data-qa="message-text"> <div class="p-block_kit_renderer" data-qa="block-kit-renderer"> <div class="p-block_kit_renderer__block_wrapper p-block_kit_renderer__block_wrapper--first"> <div class="p-rich_text_block"> <div class="p-rich_text_section">CoreWeave, the AI Hyperscaler™, acquired Weights Biases to create the most powerful end-to-end platform to develop, deploy, and iterate AI faster. Since 2017, CoreWeave has operated 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.</div> <div class="p-rich_text_section"><br>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.</div> <div class="p-rich_text_section"><br>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.</div> <div class="p-rich_text_section"><br>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.</div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div></div><h3><strong>What You’ll Do:</strong></h3> <p>As a software engineer on the Sweeps team, you’ll take end-to-end ownership of a user-facing product that helps practitioners design and run hyperparameter searches. You’ll balance maintaining existing systems with building new functionality, and regularly debug real user workflows that span backend logic, the UI, and user-run agents.</p> <p>Sweeps is a core part of the WB product, and changes you make will directly affect how users configure experiments, run workloads on their own infrastructure, and reason about results.</p> <p><strong>About the role:</strong></p> <ul> <li>Own the development and evolution of the Sweeps product, maintaining existing systems while designing and shipping new functionality with a focus on backend logic and APIs</li> <li>Implement and evolve sweep semantics and hyperparameter generation logic</li> <li>Debug and resolve user-reported issues that may involve backend behavior, agent execution, or UI interactions</li> <li>Improve reliability, performance, and correctness of sweep execution as usage scales</li> <li>Build and maintain integrations between Sweeps and ex ... (truncated, view full listing at source)