Anthropic’s Human Data Platform team builds systems that collect data to improve AI models, including infrastructure to simulate real‑world environments, interfaces for data vendors, and pipelines that enable researchers to gather high‑quality data at scale. As Claude’s real‑world usage evolves, so do our data needs—requiring rapid prototyping and shipping. You will work closely with engineering, research, data ops, and external vendors to prioritize tooling, identify high‑leverage investments, and translate learning into clear product direction.
Product Management, Human Data Platform at Anthropic
Hybrid - San Francisco, CA, United States; New York City, NY, United States
More jobs at AnthropicSalary
USD 305,000 - 385,000
Requirements
Skills
- Believe that advanced AI systems could have a transformative effect on the world
- Experience shipping products requiring deep understanding of technical constraints
- Experience working directly with research teams, ideally in AI/ML contexts
- Comfortable communicating with crowdworkers and research teams about data quality
- 5+ years in product management, launching new products and scaling existing products
- Intellectual curiosity and autonomous learning ability
- Experience building data collection tools, annotation platforms, or human-in-the-loop pipelines
- Strong project management skills: prioritization, communication across teams and org boundaries
Responsibilities
- Own the product direction for human data tooling, prioritizing labeling interfaces, infrastructure investments, data quality, and operational visibility
- Partner with engineering to scope and ship quickly in a fast‑moving prototyping environment
- Develop deep understanding of research and training approaches to identify high‑leverage tooling investments
- 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
Technologies
Human data toolingLabeling interfacesInfrastructureData pipelinesAI/MLAnnotation platformsHuman‑in‑the‑loop pipelines
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