ML Research Engineer — Health AI & Radar Sensing

Circadia Health; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Circadia Health is seeking an ML Research Engineer to research, design, and deploy next-generation models for our clinical monitoring platform. You will work on radar-based sensing, integrate EHR data, and push research into production on cloud and edge devices.

Reporting to the Principal ML Engineer, you will experiment with rigorous methods, translate papers into code, and collaborate with clinical and data teams to validate algorithms for regulatory approval and real-world impact.

Qualifications

• Master's degree in Computer Science, ML, Data Science or a related quantitative field.
• Proficient production-grade Python coding.
• Strong understanding of classical ML techniques with real-world application.
• Deep learning experience with PyTorch, TensorFlow or JAX and quick paper-to-code translation.

Responsibilities

• Research and develop novel models for Circadia's platform, including radar-based sensing and clinical data integration.
• Design and run rigorous experiments with clear hypotheses and reproducible results.
• Deploy models for cloud and on-device inference with attention to latency and memory.
• Collaborate with clinical research, signal processing and data teams to validate algorithms and support regulatory submissions.

Skills

Python

ML experimentation

Communication

Experimentation

Scientific mindset

Code quality

Education

Master's degree in Computer Science / ML / Data Science / Mathematics

Tools

Docker

Flask

FastAPI

PyTorch

TensorFlow

JAX

Job description

Circadia Health is seeking an ML Research Engineer to research, design, and deploy next-generation models for our clinical monitoring platform. You will work on radar-based sensing, integrate EHR data, and push research into production on cloud and edge devices.

Reporting to the Principal ML Engineer, you will experiment with rigorous methods, translate papers into code, and collaborate with clinical and data teams to validate algorithms for regulatory approval and real-world impact.