Product Management, Human Data Platform

Anthropic Anthropic · AI Frontier · San Francisco, CA · Product Management, Support, & Operations

Product Manager for Anthropic's Human Data Platform, focusing on building systems to collect data that improves AI models. Responsibilities include owning product direction for data tooling, partnering with engineering, understanding research and training approaches, identifying patterns for reusable infrastructure, understanding vendor pain points, and defining KPIs related to data collection and model impact.

What you'd actually do

  1. Own the product direction for our human data tooling, with clear prioritization across labeling interfaces, infrastructure investments, data quality, and operational visibility
  2. Partner with engineering to scope and ship quickly, staying close to the work in a fast-moving prototyping environment
  3. Develop a deep understanding of research and training approaches to identify where tooling investments will have the highest leverage
  4. Identify patterns across one-off requests and push toward reusable infrastructure that compounds over time
  5. Sit in on crowd worker and vendor sessions to systematically understand pain points

Skills

Required

  • Product direction
  • Prioritization
  • Labeling interfaces
  • Infrastructure investments
  • Data quality
  • Operational visibility
  • Engineering partnership
  • Prototyping
  • Research and training approaches
  • Tooling investments
  • Reusable infrastructure
  • Crowd worker and vendor sessions
  • Outcome-based KPIs
  • Technical constraints
  • AI/ML contexts
  • Human interaction with AI systems
  • Data elicitation design
  • Data collection tools
  • Annotation platforms
  • Human-in-the-loop pipelines
  • Researcher collaboration
  • User experience
  • Complex UI interactions
  • Annotation workflows
  • Project management
  • Intellectual curiosity
  • Autonomous learning
  • Researcher EQ
  • Product creativity
  • Founder mentality

Nice to have

  • Good instincts and an eye for intuitive user experiences

What the JD emphasized

  • shipped products where they had to deeply understand technical constraints
  • Experience building data collection tools, annotation platforms, or human-in-the-loop pipelines

Other signals

  • improves our models
  • collect data that improves our models
  • gather high-quality data at scale
  • tooling that scales
  • data quality methodology