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[PIP] Product Management, Human Data Platform

Own product direction for human data tooling at Anthropic, building labeling interfaces, infrastructure, and pipelines that enable researchers to gather high-quality training data at scale. Requires experience shipping technical products and working directly with AI/ML research teams.

305k – 385kSan Francisco, CANew York, NYProduct ManagementHybrid5+ YOE

About the role

Responsibilities

  • Own the product direction for our human data tooling, with clear prioritization across labeling interfaces, infrastructure investments, data quality, and operational visibility
  • Partner with engineering to scope and ship quickly, staying close to the work in a fast-moving prototyping environment
  • Develop a deep understanding of research and training approaches to identify where tooling investments will have the highest leverage
  • Identify patterns across one-off requests and push toward reusable infrastructure that compounds over time
  • Sit in on crowd worker and vendor sessions to systematically understand pain points
  • Define and track outcome-based KPIs: time-to-launch for new data collection projects, end-to-end data quality scores, and measurable impact on model evaluation scores

Requirements

  • Shipped products where you had to deeply understand technical constraints, not just translate requirements
  • Experience working directly with research teams, ideally in AI/ML contexts
  • Comfortable talking to crowdworkers about their workflow and to research teams about data quality methodology
  • Quick study with ability to understand a large number of different complex technical systems at a high level
  • Interest in how humans interact with AI systems and how to design experiences that elicit high-quality data
  • Bachelor's degree or equivalent combination of education, training, and/or experience in a relevant field

Nice-to-Haves

  • Experience building data collection tools, annotation platforms, or human-in-the-loop pipelines
  • Experience working with researchers who are internal users/customers
  • Good instincts and an eye for intuitive user experiences, particularly those involving complex UI interactions or annotation workflows
  • Strong project management skills: prioritization, communicating across team/org boundaries

Skills

Product ManagementAi/Ml Research CollaborationData Collection ToolingHuman-In-The-Loop PipelinesAnnotation PlatformsData Quality MethodologyTechnical Product StrategyKpi DefinitionCross-Functional CollaborationUser Research

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