KOS AI is developing the next generation of non-invasive metabolic monitoring technology. The AI Researcher will focus on creating advanced algorithms for interpreting multimodal physiological ...
Kos Ai
1 job near Columbus, OH
KOS AI is developing the next generation of non-invasive metabolic monitoring technology. The AI Researcher will focus on creating advanced algorithms for interpreting multimodal physiological ...
Full-time
Re-posted 29 days ago
Job description
Job Summary:
KOS AI is developing the next generation of non-invasive metabolic monitoring technology. The AI Researcher will focus on creating advanced algorithms for interpreting multimodal physiological signals and modeling dynamic biological processes, contributing to the core intelligence of the product.
Responsibilities:
• Development of new feature extraction methods for optical signals, motion signals, and physiological biomarkers
• Design of noise-resilient, motion-resilient, and artifact-robust representations
• Exploration of frequency-based, time-domain, and hybrid feature spaces
• Discovery of patterns that reflect underlying biological processes
• Research and implementation of models capable of learning from complex, noisy, and high-variability biological data
• Development of ensemble systems, temporal models, and context-aware learning frameworks
• Design of robust inference pipelines capable of running efficiently on constrained environments
• Integration of uncertainty, confidence scoring, and adaptive filtering
• Modeling of dynamic processes related to human physiology, metabolism, and behavioral context
• Exploration of relationships between physiological signals, daily patterns, and state transitions
• Development of personalized data adaptation methods that learn individual physiological baselines and trends
• Research on forecasting trends and physiological trajectories
• Identification of behavioral and biological events from multimodal data
• Development of systems that adapt to real-world, irregular, and incomplete signals
• Working with diverse datasets collected across multiple conditions
• Data cleaning, harmonization, and statistical evaluation
• Designing experiments to validate new features, models, and interpretation techniques
Qualifications:
Required:
• Strong foundations in machine learning, time-series modeling, or signal processing
• High proficiency in Python and modern deep learning frameworks
• Experience working with noisy, real-world, or multimodal data
• Ability to explore scientific literature and convert insights into working algorithms
• Curiosity, creativity, and a strong desire to work on difficult open-ended problems
Preferred:
• Research experience with biomedical signals or physiological modeling
• Background in optical sensing, human physiology, or biosignal analytics
• Experience working with low-power or resource-constrained inference environments
• Familiarity with probabilistic modeling, uncertainty quantification, or ensemble systems
• Demonstrated ability to design and carry out empirical research
Company:
Kos provides real-time, interactive and cost-effective healthcare using a wearable technology and AI/ML proprietary system. Founded in 2020, the company is headquartered in Palo Alto, California, US, , with a team of 11-50 employees. The company is currently Early Stage.
KOS AI is developing the next generation of non-invasive metabolic monitoring technology. The AI Researcher will focus on creating advanced algorithms for interpreting multimodal physiological signals and modeling dynamic biological processes, contributing to the core intelligence of the product.
Responsibilities:
• Development of new feature extraction methods for optical signals, motion signals, and physiological biomarkers
• Design of noise-resilient, motion-resilient, and artifact-robust representations
• Exploration of frequency-based, time-domain, and hybrid feature spaces
• Discovery of patterns that reflect underlying biological processes
• Research and implementation of models capable of learning from complex, noisy, and high-variability biological data
• Development of ensemble systems, temporal models, and context-aware learning frameworks
• Design of robust inference pipelines capable of running efficiently on constrained environments
• Integration of uncertainty, confidence scoring, and adaptive filtering
• Modeling of dynamic processes related to human physiology, metabolism, and behavioral context
• Exploration of relationships between physiological signals, daily patterns, and state transitions
• Development of personalized data adaptation methods that learn individual physiological baselines and trends
• Research on forecasting trends and physiological trajectories
• Identification of behavioral and biological events from multimodal data
• Development of systems that adapt to real-world, irregular, and incomplete signals
• Working with diverse datasets collected across multiple conditions
• Data cleaning, harmonization, and statistical evaluation
• Designing experiments to validate new features, models, and interpretation techniques
Qualifications:
Required:
• Strong foundations in machine learning, time-series modeling, or signal processing
• High proficiency in Python and modern deep learning frameworks
• Experience working with noisy, real-world, or multimodal data
• Ability to explore scientific literature and convert insights into working algorithms
• Curiosity, creativity, and a strong desire to work on difficult open-ended problems
Preferred:
• Research experience with biomedical signals or physiological modeling
• Background in optical sensing, human physiology, or biosignal analytics
• Experience working with low-power or resource-constrained inference environments
• Familiarity with probabilistic modeling, uncertainty quantification, or ensemble systems
• Demonstrated ability to design and carry out empirical research
Company:
Kos provides real-time, interactive and cost-effective healthcare using a wearable technology and AI/ML proprietary system. Founded in 2020, the company is headquartered in Palo Alto, California, US, , with a team of 11-50 employees. The company is currently Early Stage.