Description

You will bridge the gap between science and production by building robust ML models that handle complex health data while ensuring all systems remain reliable, ethical, and compliant.

Requirements

• •Advanced degree in relevant quantitative field
• •Scientific reasoning in ML model design
• •Research experience with health-related data
• •Experience applying ML in production
• •Strong grounding in statistical methods
• •Hands-on experience with ML Ops
• •Experience with cloud-based infrastructure
• •Clear communication of technical concepts
• •Experience in regulated environments
• •Deep scientific and applied ML experience

Tasks

• •Design and maintain science-based machine learning models
• •Apply scientific reasoning to model design and validation
• •Build robust models using health-related data and biometric signals
• •Translate research insights into production-ready ML systems
• •Manage the end-to-end machine learning lifecycle
• •Define and evolve reliable ML operational practices
• •Ensure high-quality data inputs and evaluation pipelines
• •Integrate health-specific models with other AI components
• •Operate ML systems according to privacy and regulatory standards

Tools & Technologies

Benefits