Amigo builds trust and safety infrastructure for AI in mission-critical environments, partnering with organizations in healthcare and other regulated sectors to deploy AI systems that operate reliably when the stakes are highest. Their infrastructure enables verification, monitoring, and real-time oversight—ensuring AI serves people safely at scale.
Requirements
- Strong background in statistical inference and experimental design
- Experience with Bayesian methods and uncertainty quantification
- Track record of building statistical models for real-world applications
- Knowledge of risk modeling and decision theory
- Understanding of healthcare data and clinical decision-making
- Background in medical statistics or biostatistics
- Experience with safety-critical systems and risk assessment
Responsibilities
- Design statistical frameworks that provide quantified confidence in system behavior
- Build risk modeling systems that help organizations assess system deployment decisions
- Create confidence scoring algorithms that accurately reflect system reliability
- Develop methods for handling rare but critical events in healthcare applications
- Design A/B testing frameworks that maintain safety while measuring improvements
- Collaborate with healthcare experts to ensure statistical models reflect clinical reality
Other
- Collaborate with healthcare experts to ensure statistical models reflect clinical reality
- Healthcare or regulated industry experience
- Knowledge of healthcare compliance and regulatory requirements
