Machine Learning Engineer - Signal Processing

Machine Learning Engineer - Signal Processing

Our client is revolutionising healthcare for millions of patients worldwide, combining over two decades of proprietary wearable technology with clinically relevant signals. They are seeking a Machine Learning Engineer with a passion for developing impactful healthcare solutions using wearable data. This high-impact role offers the opportunity to shape the future of digital health and bring clinically validated, regulatory-ready ML solutions to market.

The ideal candidate for this Machine Learning Engineer position brings a wealth of experience in applying machine learning to time-series or physiological data. With a strong foundation in signal processing and time-series modelling, you're proficient in Python and familiar with ML frameworks such as PyTorch or TensorFlow. Your understanding of FDA regulatory pathways for medical software will be crucial in this role. Experience with MLOps practices and model versioning in compliant environments will also be highly beneficial.

Minimum 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 modelling.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Familiarity with FDA regulatory pathways for medical software and standards like IEC 62304 or ISO 13485.
• Experience with MLOps practices and model versioning in compliant environments.

About the Job:

Contract Type: Permanent