ML Engineer- Series C HealthTech -Signal Processing
Join this Silicon Valley HealthTech scale up to make real impact on patient's lives. This role is fully remote within the UK, but this company don't provide visa sponsorship.
About the Role
We are seeking a Machine Learning Engineer to develop real-time ML solutions using wearable and physiological sensor data. You will work on scalable algorithms for continuous biosignal analysis in regulated healthcare environments, contributing to production-grade digital health technologies and clinically oriented ML systems.
- Design, build, and optimize machine learning models for real-time analysis of wearable biosignal data, including ECG, PPG, accelerometer, and related sensor streams.
- Develop and validate algorithms capable of achieving clinical-grade performance in regulated environments.
- Process and manage large-scale continuous time-series datasets generated by wearable devices and connected sensors.
- Collaborate cross-functionally with engineering, product, clinical, and compliance stakeholders to align solutions with healthcare software and regulatory requirements.
- Optimize ML pipelines and inference workflows for deployment on edge, mobile, or embedded platforms with constrained compute resources.
- Conduct validation and benchmarking experiments using metrics such as sensitivity, specificity, ROC-AUC, precision, recall, and related statistical measures.
- MS or PhD in Machine Learning, Biomedical Engineering, Computer Science, Electrical Engineering, or a related technical discipline.
- 3-5+ years of experience applying machine learning techniques to time-series, biosignal, or physiological datasets.
- Strong understanding of signal processing, time-series analytics, anomaly detection, deep learning, and classical machine learning approaches.
- Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
- Familiarity with healthcare software development standards and regulated software environments, including concepts related to SaMD, GMLP, IEC 62304, ISO 13485, or equivalent frameworks.
- Experience with MLOps practices, model lifecycle management, CI/CD workflows, and version-controlled ML deployment pipelines.
real-time analysis; time-series and continuous data; FDA; Python; PyTorch; TensorFlow; Healthcare Data
Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates