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Weights & Biases · 22 hours ago

Staff Product Manager, Sweeps and Launch- Weights & Biases

Sunnyvale, CA

Full-time

Hybrid

Senior Level, Lead/Staff

$188K/yr - $275K/yr

7+ years exp

Weights & Biases, acquired by CoreWeave, is focused on creating a powerful platform for AI development and deployment. The Staff Product Manager will oversee the Launch and Sweeps product areas, driving product vision and execution to enhance deep learning workflows for AI practitioners.

Artificial Intelligence (AI)Data VisualizationDeveloper ToolsGenerative AIMachine Learning

Comp. & Benefits

No H1B

U.S. Citizen Only

Responsibilities

Own the Launch and Sweeps product roadmap, defining how AI researchers discover optimal hyperparameters, scale their training and eval jobs, and prepare models for inference

Collaborate deeply with customers and deep learning practitioners to understand pain points around job orchestration, distributed training, LLM evaluation workflows, compute resource management, and hyperparameter optimization—then translate those insights into product improvements

Drive execution across cross-functional teams, coordinating with engineering, design, platform infrastructure, and go-to-market to rapidly ship capabilities users love

Prioritize with intention, making trade-offs across performance, reliability, scalability, and developer velocity to ensure Launch and Sweeps deliver value to the most discerning customers in the industry

Elevate the developer experience by streamlining workflows for creating Launch jobs, configuring sweep strategies, visualizing hyperparameter impact and exploration, and parallelizing agents across compute clusters

Communicate exceptionally, keeping multiple stakeholders, engineering teams, and customers aligned with transparency, accuracy, and care

Qualification

Product managementDeep learning infrastructureHyperparameter optimizationKubernetesSLURMAPI designCross-functional influenceUser-focusedSelf-directedCareTasteClear communication

Required

7+ years as a product manager working on developer tools, deep learning infrastructure, or ML engineer platforms

End-to-end ownership of a technical product—whether a model, orchestration feature, or developer tool—all the way to production, including defining success criteria, measuring effectiveness, and iterating to improve impact and user happiness

Comfortable discussing Kubernetes and SLURM, job scheduling, hyperparameter optimization algorithms, and API design with engineers and AI researchers

Skilled at managing and influencing AI engineers, software engineers, and stakeholders—with or without official authority—to align teams and drive outcomes

Ability to seek feedback from many directions and channel it into a single, executable stream, bringing clarity and organization to complex, fast-moving environments

Strong opinions about the products you use and a high bar for developer experience