Product Management, Human Data Platform (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Product Manager (AI): Developing systems to collect high-quality human data to improve AI models with an accent on labeling interfaces and scalable data pipelines. Focus on translating research needs into technical infrastructure and optimizing the human-in-the-loop data collection process.
Location: Hybrid: Must be based in San Francisco, CA or New York City, NY (minimum 25% office presence)
Salary: $305,000 - $385,000 USD
Company
AI safety and research company focused on creating reliable, interpretable, and steerable AI systems.
What you will do
- Own the product direction for human data tooling, prioritizing labeling interfaces and infrastructure investments.
- Partner with engineering to rapidly prototype and ship scalable data collection tools.
- Collaborate with research teams and data ops to identify high-leverage tooling investments.
- Analyze crowd worker and vendor pain points to improve operational visibility and data quality.
- Define and track outcome-based KPIs, including time-to-launch and model evaluation impact.
Requirements
- Experience shipping technical products with a deep understanding of technical constraints.
- Background working with research teams, preferably in AI/ML contexts.
- Ability to communicate effectively with both crowd workers and research scientists.
- Must be based in or able to work from San Francisco or New York City (hybrid).
- Bachelor's degree or equivalent professional experience.
Nice to have
- Experience building annotation platforms or human-in-the-loop pipelines.
- Intuitive eye for complex UI interactions in annotation workflows.
- Strong project management skills across organizational boundaries.
Culture & Benefits
- Competitive compensation and optional equity donation matching.
- Generous vacation and parental leave.
- Flexible working hours and collaborative office environments.
- Visa sponsorship available for qualifying candidates.
- Collaborative "big science" research culture focusing on high-impact goals.
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