Signal Processing Engineer

Responsibilities

• Design and implement signal processing algorithms for extracting vital signs from video-based sensors (rPPG, rBP)
• Develop real-time filtering, denoising, and feature extraction methods to achieve clinical-grade accuracy
• Build validation pipelines comparing video-based measurements against clinical reference devices (ECG, PPG, BP monitors)
• Design studies to ensure millisecond-level synchronization between video streams and reference sensors
• Integrate with the computer vision pipeline using C++
• Architect cloud-based QA and automated verification systems for algorithm validation
• Prototype algorithms in Python and C++ before production deployment

Requirements

• Master's degree or PhD in Electrical Engineering, Biomedical Engineering, or a related field
• 5+ years of industry experience in signal processing for medical or physiological sensing (or PhD equivalent)
• Strong fundamentals in digital signal processing, statistical methods, and real-time systems
• Deep expertise in physiological signal processing (PPG, ECG, respiration, blood pressure)
• Proficiency in both Python and C++
• Experience with spectral analysis, adaptive filtering, and time-domain methods

Preferred Qualifications

• Experience with contact-based and contactless vital sign measurement technologies
• Background with medical-grade measurement devices and clinical reference standards
• Experience with embedded signal processing (ARM, edge devices)
• Knowledge of motion artifact removal and noise reduction
• Familiarity with DevOps practices for reproducible research
• Background in medical devices or regulated environments

About the Company

Norbert is building autonomous robots that deliver healthcare. Our AI sensing platform mounts on mobile robots to monitor patients, capture vitals without contact, and document data to EMRs, helping solve the global nursing shortage.