Research Engineer (Embedded AI/ML - MetaSense Project)
Core
Develop biocomputational AI/ML models and embedded firmware for a wearable cardiometabolic sensing platform using dual-point photoplethysmography (2PPG) and ECG.
Role type
Research Engineer (Embedded AI/ML)
Builds
Wearable biosensing systems for continuous hemodynamic biomarker tracking
Domain
Biomedical engineering / Wearable health tech / Embedded systems
Deliverable
production ML models | product features
Required skills
Python, embedded firmware development, microcontroller integration, I²C/SPI/UART protocols, signal processing, physiological data validation
Preferred skills
Experience with clinical ML model validation, knowledge of regulatory pathways (HSA/FDA), dashboard development
Technologies
Python, Git, I²C, SPI, UART, PPG, ECG
Responsibilities
Develop biocomputational AI/ML models for hemodynamic feature extraction; Assist with embedded firmware and hardware bring-up for wearable PPG/ECG sensors; Prepare and validate physiological datasets for model training; Support development of dashboards and visualization tools for sensor data and model outputs; Maintain technical documentation and collaborate with research partners.
Seniority
Junior, closely supervised IC