Staff Product Manager, Sweeps and Launch- Weights & Biases

Weights & Biases•Sunnyvale, CA

4d•$188,000 - $275,000•Hybrid

About The Position

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. W&B 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. W&B 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. 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. If you're energized by solving infrastructure challenges that directly accelerate deep learning workflows, collaborating with the world’s best AI teams, and delivering tools that move the industry frontier forward, his role is for you.

Requirements

Experience: You have 7+ years as a product manager working on developer tools, deep learning infrastructure, or ML engineer platforms.
End-to-end ownership: You've taken 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.
Technical fluency: You’re comfortable discussing Kubernetes and SLURM, job scheduling, hyperparameter optimization algorithms, and API design with engineers and AI researchers.
Cross-functional influence: You’re skilled at managing and influencing AI engineers, software engineers, and stakeholders—with or without official authority—to align teams and drive outcomes.
Clear communication: A major part of this role is seeking feedback from many directions and channeling it into a single, executable stream. You bring clarity and organization to complex, fast-moving environments.
Care and taste: You have strong opinions about the products you use and a high bar for developer experience.

Nice To Haves

Experience with deep learning frameworks (PyTorch, JAX), distributed training, or LLM development workflows.
Hands-on experience with SLURM or Kubernetes for GPU-intensive workloads.
Prior exposure to W&B or other experiment-tracking and model management platforms.
Understanding of hyperparameter optimization methods and evaluation workflows for large models.

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.