Signal Processing Research Engineer

About Circadia Health Circadia Health is a growth-stage healthcare harwdare & AI company on a mission to prevent avoidable hospitalizations and transform senior-care operations. Our AI Care System combines:

• Contactless sensing that monitors respiration and motion with medical-grade accuracy — powered by our own in-house-designed monitoring devices, developed from the radar hardware up
• Native predictive models that detect 85% of preventable adverse events several days in advance
• Enterprise integrations that operationalize predictions directly inside EHR, care-coordination, billing, and compliance workflows

Today, our technology touches 40,000+ post-acute patients daily across skilled-nursing, home-health, and home-care networks. Because we build our own sensing hardware and the algorithms that run on it, our signal processing work reaches from raw radar waveforms all the way to clinical decisions. We are backed by leading healthcare and AI investors, with offices in Los Angeles and London.

About the Role

What you'll do

• Develop novel signal processing algorithms for Circadia's contactless monitoring system (radar and other sensors)
• Research signal processing techniques — and, where useful, machine learning — to extract clinically relevant features from sensor data
• Process data from clinical studies to develop and validate product features
• Prepare algorithm documentation for regulatory compliance and IP protection
• Implement algorithms for execution on embedded devices
• Work with the Product, Clinical Research and Engineering teams (Algorithms, Data Science, Electronics, Firmware) to align on requirements
• Provide regular progress updates and reports to management

About you

• MSc or PhD in signal processing, electrical engineering, biomedical engineering, or a related field
• Strong, demonstrable expertise in signal processing — this is the core of the role
• Industry work experience as an algorithm or signal processing engineer (beyond academic research)
• A track record of building algorithms that have been deployed in real products — not solely offline processing of research datasets
• Experience working with biosignals or physiological sensor data
• Experience with sensor characterization and configuration
• Comfortable across the research-to-deployment path, including implementing algorithms on embedded/constrained devices
• Able to communicate clearly across research, clinical and engineering teams

Nice to have

• Familiarity with machine learning, or experience combining signal processing and ML approaches
• Experience with radar or other contactless sensing
• Familiarity with medical device regulatory requirements or working in a regulated environment