Senior Product Manager - Platform

Snorkel AI Snorkel AI · Data AI · Redwood City, CA +1 · 314 - Product

Senior Product Manager to own the core platform that powers all data operations across Snorkel's ecosystem. This platform enables experts to efficiently produce high-quality data, supports internal operations at scale, and provides reliable APIs and SDKs for customers. The role involves defining platform strategy, setting the roadmap, and partnering with Engineering, Research, and Operations to build scalable, reliable systems.

What you'd actually do

  1. Own the product vision, strategy, and roadmap for the core platform supporting expert contributors, internal operations, and customers.
  2. Define and deliver expert tooling, workflow orchestration systems, and internal ops controls that improve productivity, quality, and scalability.
  3. Lead platform initiatives across data ingestion, storage, versioning, permissions/IAM, and system reliability.
  4. Partner deeply with Engineering to make informed tradeoffs across APIs, data models, system architecture, and platform abstractions.
  5. Collaborate with Research and Operations to ensure platform capabilities support evolving RLHF methodologies and operational needs.

Skills

Required

  • 5–7 years of experience as a Product Manager, with ownership of complex, cross-functional product areas.
  • Experience building internal tools, ops platforms, or data platforms at scale.
  • Strong technical fluency, with comfort discussing APIs, data models, system design, and infrastructure tradeoffs with engineering teams.
  • Proven ability to own end-to-end product experiences across multiple user personas.
  • Strong analytical and problem-solving skills, with a track record of metrics-driven decision making.
  • Excellent collaboration skills and experience partnering closely with Engineering, Research, and Operations teams.

Nice to have

  • Experience building platforms that support human-in-the-loop or data production workflows.
  • Background in data infrastructure, ML platforms, or enterprise SaaS products.
  • Experience designing APIs or developer-facing platforms.
  • Demonstrated ability to lead large, cross-team initiatives without formal authority.

What the JD emphasized

  • core platform
  • data operations
  • expert tooling
  • workflow orchestration
  • data ingestion
  • storage
  • versioning
  • system reliability
  • APIs
  • data models
  • system architecture
  • platform abstractions
  • RLHF methodologies
  • operational needs
  • APIs
  • SDKs
  • platform capabilities
  • throughput
  • cycle time
  • quality
  • cost efficiency
  • platform adoption
  • reliability
  • platform bottlenecks
  • performance
  • scalability
  • experts experience
  • platform investments

Other signals

  • AI data platform
  • transform expert knowledge into specialized AI
  • build custom AI with their data