Drimva

Anthropic

Product Management, Human Data Platform

$305K–$385K

San Francisco, CA +2 · Full-time · Posted Apr 29, 2026

Location
San Francisco, CA
New York City, NY
San Francisco, California, United States
Experience
5+ years in product management; minimum years required may correlate with internal job level requirements.
Education
Bachelor’s degree or an equivalent combination of education, training, and/or experience. Relevant field of study demonstrated through coursework, training, or professional experience.
Visa sponsorship
Visa sponsorship is available, but not for every role or candidate; the company will make reasonable efforts to obtain a visa if an offer is made.

About the job

Sets product direction for human data tooling used to collect high-quality data for AI model research and training.

What you'll do

  • Prioritize and guide development of labeling interfaces, infrastructure, data quality, and operational visibility.
  • Partner with engineering and research teams to scope and ship tools, turning user and vendor feedback into reusable infrastructure.
  • Define and track outcome-based KPIs for project launch time, data quality, and model evaluation impact.

What they ask for

  • Experience shipping products while deeply understanding technical constraints.
  • Experience working directly with research teams, ideally in AI/ML contexts.
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field of study demonstrated through coursework, training, or professional experience.
  • 5+ years in product management, with experience launching new products and scaling existing products.

Nice to have

  • Experience building data collection tools, annotation platforms, or human-in-the-loop pipelines.
  • Experience working with internal researcher users/customers; strong user-experience instincts for complex interfaces or annotation workflows.

Pay

$305,000 — $385,000 USD (base salary)

AI focus

Product management for human data collection tools and pipelines that support AI model research, training, and evaluation.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 4, 2026 (UTC)