Staff Product Manager: AI Infra & Developer Tools Platform

Weights & Biases; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with employer match

Flexible PTO

Parental leave

Job summary

CoreWeave is seeking a Staff Product Manager to own a suite of infrastructure-native developer tools that bridge Weights & Biases capabilities with CoreWeave’s platform. You’ll drive product strategy, collaborate with frontier AI teams, and lead launches of advanced orchestration and workflow automation.

You’ll partner with platform engineering to align research tooling with hardware telemetry and cloud orchestration, shaping the future of AI infrastructure at scale.

Qualifications

• 7+ years as a product manager working on developer tools, deep learning infrastructure, or ML engineer platforms.
• Experience taking a technical product from conception to production, with measurable impact and user happiness.

Responsibilities

• Define and ship infrastructure-native products that connect experiment tracking with the platform.
• Own Launch (job submission) and expand its orchestration role for frontier AI workflows.
• Engage with frontier model teams to understand needs and translate them into roadmaps.
• Bridge product and platform engineering between two organizations now becoming one.
• Resolve friction in job submission, compute management, and observability workflows.
• Explore hardware-software concepts at the edge of AI platforms and automation.

Skills

Product management

Deep learning infra

Developer tools

Cross-functional leadership

Kubernetes

SLURM

Tools

Kubernetes

SLURM

Job description

CoreWeave is seeking a Staff Product Manager to own a suite of infrastructure-native developer tools that bridge Weights & Biases capabilities with CoreWeave’s platform. You’ll drive product strategy, collaborate with frontier AI teams, and lead launches of advanced orchestration and workflow automation.

You’ll partner with platform engineering to align research tooling with hardware telemetry and cloud orchestration, shaping the future of AI infrastructure at scale.