Staff Product Manager, Sweeps and Launch- Weights & Biases

<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><p><strong>What You'll Do</strong></p> <p>As a Staff Product Manager for Launch and Sweeps at Weights Biases, you'll own two foundational product areas that power how deep learning practitioners scale their work. </p> <p>WB Launch enables teams to scale experiments from a workstation to massive clusters—whether that's spinning up large distributed training runs or executing complex evaluation pipelines that feed signals back into the training process. WB Sweeps automates and advises on hyperparameter search, helping practitioners find optimal model configurations through grid, random, and Bayesian search methods. Together, these products support the workflows that matter most to teams training large models: seamlessly scaling up compute, running complex evals, and efficiently exploring the frontier of model performance. </p> <p>You'll be responsible for driving the product vision and execution for these offerings, ensuring teams training large models can design sweeps, control their exploration of the hyperparameter search space, package reproducible jobs, and orchestrate training and evaluation at scale.</p> <p>If you're energized by sol ... (truncated, view full listing at source)