About the Role
The role involves designing, developing, and optimizing machine learning models that process physiological data to deliver personalized health insights. The scientist will work closely with research, engineering, and product teams to translate scientific concepts into production-grade algorithms.
Responsibilities
- Design and implement machine learning models for physiological signal analysis
- Optimize algorithms for performance and scalability on embedded systems
- Collaborate with data scientists and engineers to integrate models into products
- Evaluate model performance using statistical and clinical validation methods
- Stay current with advancements in machine learning and biomedical signal processing
- Lead algorithm development efforts from concept to deployment
- Conduct exploratory data analysis on large-scale biometric datasets
- Improve model interpretability and reliability for consumer-facing outputs
- Support clinical validation studies with algorithmic expertise
- Document methods and results for internal and regulatory review
- Mentor junior scientists and engineers in ML best practices
- Contribute to research initiatives and technical publications
- Identify opportunities for innovation in sleep, activity, and recovery tracking
- Work with cross-functional teams to define product requirements
- Ensure compliance with data privacy and regulatory standards
- Refine data labeling pipelines to enhance training set quality
- Develop anomaly detection methods for sensor data integrity
- Apply time-series analysis techniques to longitudinal health data
- Balance model complexity with real-time processing constraints
- Support A/B testing of algorithmic changes in production
- Troubleshoot model drift and performance degradation
- Collaborate on feature engineering using domain knowledge
- Translate clinical research findings into algorithmic improvements
- Participate in technical design reviews and architecture planning
- Contribute to intellectual property development through patent filings
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid remote work model with flexibility based on location and team needs
Team
Part of a multidisciplinary team focused on health technology and wearable devices
Why This Role Matters
This position plays a critical role in shaping the scientific foundation of wearable health technology, directly influencing how users understand their sleep, activity, and recovery patterns through accurate, data-driven insights.
What We Value
We prioritize scientific rigor, user-centered design, and collaboration across disciplines to build trustworthy health tools grounded in evidence-based research and real-world validation.
Growth Opportunities
Scientists in this role have the chance to lead high-impact projects, publish research, and contribute to the evolution of health monitoring algorithms at scale.
Work Environment
The team operates in a dynamic, research-driven environment that encourages experimentation, peer review, and continuous learning while maintaining focus on product deliverables.
Impact Metrics
Success is measured by model accuracy improvements, user engagement with insights, and contributions to clinical validation outcomes.
Collaboration Style
Regular interaction with hardware engineers, data analysts, clinical researchers, and product managers ensures alignment between algorithm development and user needs.
Technology Stack
The team uses Python, PyTorch, AWS, Git, and internal data platforms to develop, test, and deploy machine learning models in a secure environment.
Research Integration
Ongoing integration of peer-reviewed findings into algorithm updates ensures that product features reflect the latest scientific understanding.
User Privacy Focus
All algorithm development follows strict data governance policies to protect user privacy and ensure compliance with global regulations.
Innovation Culture
Team members are encouraged to propose new methods, run pilot studies, and explore novel applications of biometric data for health improvement.
Available for qualified candidates requiring work authorization
