Product Lead: Human Data Platform & Data Tools

Neura Market; San Francisco (CA); Hybrid; USD 305,000 - 385,000; Full time

Job summary

Anthropic is seeking a Senior Product Manager to lead the human data tooling initiative in our SF office. You’ll partner with researchers, data operations, and external vendors to prototype, ship, and scale data labeling and infrastructure tooling that improves model quality.

You will shape priorities by understanding research needs, build reusable solutions, and drive outcomes through clear KPIs. This hybrid role requires deep collaboration across teams and vendors.

Qualifications

• Bachelor’s degree or an equivalent combination of education, training, and/or experience.
• Experience working with researchers in AI/ML contexts is a plus.
• Strong ability to translate requirements into actionable product features.

Responsibilities

• Own the product direction for 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.

Skills

Product management

Cross-functional collaboration

Data tooling

AI/ML domain familiarity

Research collaboration

Education

Bachelor's degree

Job description

Anthropic is seeking a Senior Product Manager to lead the human data tooling initiative in our SF office. You’ll partner with researchers, data operations, and external vendors to prototype, ship, and scale data labeling and infrastructure tooling that improves model quality.

You will shape priorities by understanding research needs, build reusable solutions, and drive outcomes through clear KPIs. This hybrid role requires deep collaboration across teams and vendors.