Machine Learning Engineer – Wearable Health Algorithms - Remote

Overview

all.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.

In Short

• We’re looking for a Machine Learning Engineer with a passion for developing impactful healthcare solutions using wearable data.
• You’ll 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.
• Help bring clinically validated, regulatory-ready ML solutions to market.
• Design and implement machine learning models for real-time analysis of wearable biosignal data.
• Develop algorithms that meet clinical-grade performance standards.
• Collaborate with clinical, product, and regulatory teams.
• Run thorough validation experiments including performance metrics.
• Contribute to technical documentation and regulatory submissions.
• Starting pay will be determined based on various factors.

Requirements

• MS or PhD in Machine Learning, Biomedical Engineering, Computer Science, or a related field.
• 3–5+ years of experience applying machine learning to time-series or physiological data.
• Strong foundation in signal processing and time-series modeling.
• Proficient in Python and ML frameworks such as PyTorch or TensorFlow.
• Familiarity with FDA regulatory pathways for medical software.
• Experience with MLOps practices and model versioning.

Benefits

• Opportunity to work on impactful healthcare solutions.
• Collaborative work environment with clinical and regulatory teams.
• Potential for career growth in the digital health space.
• Flexibility of remote work.
• Competitive compensation based on skills and experience.