---
title: 'ML Research Engineer at Circadia Health'
canonical: 'https://feeny.ai/job/ml-research-engineer-circadia-health-vauxhall-2wb5ca8jzvy3'
type: 'job'
last_seen: '2026-09-10'
---

# ML Research Engineer at Circadia Health

- **Company:** Circadia Health
- **Location:** Vauxhall, London, United Kingdom
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-02-23
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.lever.co/circadiahealth/5653eece-31a2-4822-8285-f3c17835fad4

## Job description

Position Overview

As an ML Research Engineer at Circadia Health, you will research, design, and build the next generation of models and algorithms that power our clinical monitoring platform. Circadia's devices use radar to continuously and contactlessly capture respiratory rate, heart rate, and movement data from thousands of patients – alongside audio and other physiological signals. This continuous sensing data is paired with deep clinical context from EHR integrations including conditions, medications, clinical notes, and care events, resulting in a dataset of extraordinary scale and depth that we've only begun to tap. Your work will push into novel problem domains: physiological foundation models, patient activity monitoring, radar-based bed-exit detection, and voice-based phenotyping – turning research ideas into production-grade systems that run on Circadia's devices and cloud infrastructure.

Reporting to the Principal ML Engineer, you will work at the intersection of research and engineering: formulating hypotheses, designing experiments, implementing models, and deploying them into real clinical environments. You will collaborate closely with clinical research, signal processing, and data teams to validate algorithms, define data collection requirements, and support regulatory approval.

This role requires a strong scientific mindset paired with a deployment-first mentality. We're looking for someone who can rapidly translate research papers into working code, iterate through experiments with rigor, and ship models that perform reliably on real patient data.

## Key Responsibilities

- Research and develop novel models and algorithms that will form the foundation of Circadia's next-generation AI capabilities, including patient activity monitoring, physiological foundation models, radar-based bed-exit detection, and voice-based phenotyping.
- Stay current with relevant ML research and rapidly prototype ideas from the literature, adapting them to Circadia's problem domains and data modalities.
- Formulate, design, run, and learn from experiments with scientific rigor, maintaining clear hypotheses, controlled comparisons, and reproducible results.
- Implement and adapt models to function effectively and efficiently in deployment environments, including both cloud infrastructure and on-device inference on Circadia's clinical monitoring hardware.
- Work with ML Ops and backend engineering teams to ensure models meet production requirements for latency, memory, reliability, and maintainability.
- Optimise models for constrained compute environments where needed (e.g. quantisation, distillation, efficient architectures).
- Work closely with clinical research teams to design validation studies, define performance benchmarks, and generate evidence to support regulatory approval.
- Help define future-proof technical and data collection requirements in conjunction with clinical and signal processing teams, ensuring research efforts are grounded in clinical utility.
- Document technical methods, experimental results, and architectural decisions for internal and external consumption.
- Present research findings to technical and non-technical stakeholders, including clinical partners and leadership.
- Contribute to publications, white papers, or regulatory submissions as needed.

Required Qualifications

- Master's degree in Computer Science, Machine Learning, Data Science, Mathematics, or another highly quantitative field.
- Ability to write production-grade, maintainable code in Python.
- Solid understanding of classical machine learning techniques with experience applying them to real-world problems.
- Strong knowledge of deep learning methods and frameworks (e.g. PyTorch, TensorFlow, JAX) with an ability to quickly implement research papers into production-grade code.
- Strong scientific mindset: ability to rapidly iterate by formulating, running, and learning from experiments.
- Strong written and oral communication skills, both technical and non-technical.

## Preferred Qualifications

- 3+ years of experience in an ML role with both research and engineering components.
- PhD in Computer Science, Machine Learning, Data Science, Mathematics, or another highly quantitative field.
- Experience with cloud computing platforms (e.g. AWS, GCP, Azure) and deployment of models into production (e.g. Docker, Flask, FastAPI).
- Experience working with data from IoT devices or sensors (e.g. radar, PPG, ECG),  particularly in a medical or health context.
- Experience with (or openness to) accelerating work using AI coding tools.
- Evidence of exceptional competence through one or more of: high-quality first-author publications in AI/ML, significant open-source contributions, strong performance in ML competitions, or standout hackathon results.

## What You Bring

- You combine research creativity with engineering discipline - you're as comfortable reading papers as you are shipping code.
- You think in experiments: you form hypotheses, test them rigorously, and iterate quickly.
- You care about clinical impact and are motivated by building technology that directly improves patient care.
- You're comfortable working in a startup environment where you'll move fast and operate with high autonomy.
- You communicate complex technical ideas clearly to both engineers and clinicians.

## Why Circadia Health

Circadia Health is redefining patient monitoring through contactless sensing and AI-driven clinical insights. As we scale from tens of thousands to hundreds of thousands of monitored patients, our data infrastructure is central to everything we do.

You’ll have the opportunity to:

- Work on real-world healthcare problems with measurable patient impact
- Build data systems that power clinical-grade AI and ML
- Take ownership in a fast-growing, mission-driven company
- Collaborate with a highly skilled, multidisciplinary team

## About Circadia Health

## Company Overview
- **One-liner**: Circadia Health provides the world’s first FDA-cleared contactless patient monitoring platform that uses radar and AI to detect early signs of clinical deterioration in senior care settings.
- **Entity Type**: Private (total funding $100.4M, multiple rounds including seed, convertible notes, and product crowdfunding)
- **Headquarters**: Los Angeles, California, United States
- **Founded**: 2016
- **Founders**: Michal Maslik (CTO & Co-Founder); other co-founders not publicly named in available sources

## Core Business
- **Primary industry**: Medical Equipment Manufacturing / Healthcare Technology
- **Target customers**: B2B – skilled nursing facilities (SNFs), senior living communities, home health agencies, and healthcare providers serving elderly populations
- **Mission statement**: “Reduce rehospitalizations by helping providers see changes in their patient’s health before they worsen and disrupt treatment.” [circadia.health/about](https://circadia.health/about)

## Products & Services
- **C200 Device**: FDA-cleared contactless monitoring device that uses radar and proprietary algorithms to detect heart rate, respiratory rate, bed exits, and motion. Includes two-way audio for patient communication. [circadiahealth.com](https://circadiahealth.com/)
- **Clinical Intelligence Platform**: Cloud-based software providing predictive analytics, real-time alerts, and daily risk reports powered by AI and machine learning. Integrates with electronic health records.
- **Virtual Nurse Monitoring Service**: A team of virtual nurses reviews device data and patient records 24/7/365 to deliver personalized, predictive risk alerts, enabling early intervention.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding of $100.4M (latest reported convertible note of $100M in 2017, plus seed and earlier rounds) [linkedin.com](https://www.linkedin.com/company/circadia)
- **Notable Investors**: Village Global (led seed round, backed by Bill Gates, Jeff Bezos, Mark Zuckerberg) [apply.workable.com](https://apply.workable.com/circadia-health/)
- **Growth Signals**:
  - 30K+ patients monitored per day [circadiahealth.com](https://circadiahealth.com/)
  - 30% reduction in rehospitalizations reported
  - 78 employees (+35.6% YoY), with presence in 6 countries [linkedin.com](https://www.linkedin.com/company/circadia)
  - Active hiring: 10 open positions, job postings up 400% YoY
  - $316K yearly ROI per 100-bed SNF claimed

## Competitive Advantages
- **First-mover with FDA clearance**: Only contactless monitoring system cleared by the FDA for heart rate, respiratory rate, and motion without any body-worn sensors.
- **Proprietary radar + AI**: Hardware, algorithms, and software all built in-house, creating a vertically integrated solution.
- **Predictive, not reactive**: Platform detects changes hours to days before clinical events (e.g., CHF, COPD exacerbation, sepsis, falls).
- **Covered by Medicare**: Reimbursable in skilled nursing facilities, lowering adoption barriers.

## Strategic Focus
- **Proactive senior care**: Continue reducing hospital readmissions and fall risks through early detection.
- **Clinical evidence generation**: Hiring a Senior Scientist for Real-World Evidence and Outcomes to publish rigorous studies proving impact.
- **Scaling clinical services**: Expanding virtual nurse monitoring and telehealth NP roles to support providers.
- **Global expansion**: Already operating in the UK, Pakistan, Germany, and Qatar.

## Why Work Here
- **Culture**: Mission-driven team of engineers, scientists, and physicians focused on transforming senior care. Emphasis on diversity and inclusion. [circadia.health/about](https://circadia.health/about)
- **Work model**: Hybrid – 2-3 days per week in the El Segundo, CA office for most roles.
- **Compensation**: Transparent salary ranges (e.g., Nurse Practitioner $120K–$160K, Senior Scientist $165K–$205K) [linkedin.com](https://www.linkedin.com/company/circadia)
- **Engineering culture**: In-house development of hardware, AI, and software; opportunities to work on cutting-edge radar and machine learning technology.
- **Growth**: Rapidly scaling team (+35.6% YoY) with roles across engineering, clinical, customer success, and data.

## Sources
1. [circadiahealth.com](https://circadiahealth.com/)
2. [circadia.health/about](https://circadia.health/about)
3. [linkedin.com/company/circadia](https://www.linkedin.com/company/circadia)
4. [apply.workable.com/circadia-health](https://apply.workable.com/circadia-health/)
5. [jobs.lever.co/circadiahealth](https://jobs.lever.co/circadiahealth)

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