Machine Learning Engineer - Hybrid Remote

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Machine Learning Engineer Wearable Health Algorithms Join to apply for the Machine Learning Engineer Wearable Health Algorithms role at all.health
Machine Learning Engineer Wearable Health Algorithms
Join to apply for the Machine Learning Engineer Wearable Health Algorithms role at all.health
health is at the forefront of revolutionizing healthcare for millions of patients worldwide. Combining more than 20 years of proprietary wearable technology with clinically relevant signals, all.health connects patients and physicians like never before with continuous, data-driven dialogue. This unique position of daily directed guidance stands to redefine primary care while helping people live happier, healthier, and longer.
Were looking for a Machine Learning Engineer with a passion for developing impactful healthcare solutions using wearable data. Youll play a key role in building real-time, FDA-compliant algorithms that analyze continuous physiological signals from wearables. This is a high-impact role with the opportunity to shape the future of digital health and help bring clinically validated, regulatory-ready ML solutions to market
Design and implement machine learning models for real-time analysis of wearable biosignal data (e.g., Develop algorithms that meet clinical-grade performance standards for use in regulated environments
Collaborate with clinical, product, and regulatory teams to ensure solutions align with FDA, SaMD, and GMLP requirements.Optimize algorithms for deployment on resource-constrained devices (e.g., Run thorough validation experiments including performance metrics like sensitivity, specificity, ROC-AUC, and precision-recall
Contribute to technical documentation and regulatory submissions for medical-grade software
MS or PhD in Machine Learning, Biomedical Engineering, Computer Science, or a related field
~35+ years of experience applying machine learning to time-series or physiological data
~ Strong foundation in signal processing and time-series modeling (e.g., deep learning, classical ML, anomaly detection)
~ Proficient in Python and ML frameworks such as PyTorch or TensorFlow
~ Familiarity with FDA regulatory pathways for medical software (e.g., Experience building ML models with wearable data (e.g., Exposure to embedded AI or edge model deployment (e.g., TensorFlow Lite, Core ML, ONNX)
Knowledge of healthcare data privacy and security (e.g., Familiarity with GMLP (Good Machine Learning Practice) and clinical evaluation frameworks
Employment type Full-time

Job function Engineering and Information Technology
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Location:
London
Job Type:
FullTime

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