Senior Software Engineer, Weave - Weights & Biases

Weights and Biases
San Francisco (Hybrid)$175k – $275kPosted 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 data-start="93" data-end="115"><span style="font-size: 10pt;"><strong data-start="97" data-end="115">What You’ll Do:</strong></span></h3> <p data-start="116" data-end="352"><span style="font-size: 10pt;">Weave is our new lightweight toolkit for tracking and evaluating GenAI applications. Our users rely on Weave to understand and improve their AI-powered products — from Agents to Retrieval Augmented Generation (RAG) systems and beyond.</span></p> <h3 data-start="354" data-end="378"><span style="font-size: 10pt;"><strong data-start="358" data-end="376">About the Role:</strong></span></h3> <p data-start="379" data-end="816"><span style="font-size: 10pt;">We’re looking for Software Engineers to help build and scale Weave. In this foundational role on a small but growing team, you’ll design and ship core functionality, gather feedback directly from early adopters, and continuously improve the product experience. You’ll work closely with cutting-edge AI builders, developing the next generation of tools that help teams understand, evaluate, and iterate on their GenAI applications.</span></p> <ul data-start="828" data-end="1336"> <li style="f ... (truncated, view full listing at source)