Machine Learning Engineer – Optical Blood Pressure Estimation

vor 2 Wochen

Neuenburg, Neuenburg, Schweiz Consult & Pepper AG Vollzeit

Your Role

  • Optical Signal Modelling & ML Development: Design, develop, and refine machine-learning models that estimate blood pressure from optical data (PPG/rPPG, RGB video) captured via smartphone cameras
  • Signal Processing & Feature Extraction: Work hands-on with camera-derived biomedical signals, applying optical and physiological signal-processing methods to build robust input pipelines
  • Model Improvement & Iterative Experimentation: Analyze model behaviour, run systematic experiments, and drive continuous iteration to enhance accuracy, robustness, and generalization across diverse conditions
  • Production Readiness & Deployment Support: Prepare ML models for deployment on mobile devices and cloud systems, collaborating with engineering to ensure smooth integration and medical-grade reliability
  • End-to-End Ownership of the Modelling Pipeline: Take full responsibility for the ML workflow—from data preparation to modelling, validation, documentation, refinement, and performance tracking
  • Cross-Functional Collaboration: Work closely with colleagues in AI/Data Science, engineering, physiology, and software to ensure solutions are technically sound and aligned with product needs
  • Leading Role in Optical BP Estimation: Advance a novel ML technology application: shape, optimize, and mature an emerging ML capability central to the Hilo Lens product line

Your Profile

  • Academic Background
    MSc or PhD in Computer Science, Machine Learning, Mathematics, Electrical Engineering, Biomedical Engineering, or a related technical field
  • Professional Expertise
    Minimum 2 years of applied industry experience in machine learning or deep learning, ideally in MedTech or regulated domains. You have hands-on experience developing, fine-tuning, iterating, and validating neural network models on real-world datasets, including conducting systematic experiments and driving performance improvements through continuous evaluation
  • Technical Experience
    You have strong programming skills in Python and hands-on experience with modern ML frameworks. You are skilled in building, validating, and deploying machine-learning models and bring a solid foundation in statistical learning and time-series modelling, including CNNs and RNNs. In addition, you bring applied signal-processing experience, particularly with PPG, ECG, or motion-supported signals.
  • Industry Fit
    Ideally, you bring experience from start-ups or innovation-driven environments with broad, end-to-end ownership, and exposure to regulated or technically demanding industries, computer vision, or sensor technology
  • Language Skills
    English at highly proficient level is a must. French, German or Italian are advantageous.
  • Personality
    A creative, proactive problem-solver, you enjoy turning complex challenges into real, working solutions. You love getting hands-on — building, testing, and iterating end-to-end — and you naturally take ownership of your work. You stay organized, move things forward independently, and collaborate openly with the people around you.

We're looking for a hands-on builder who has developed, iterated, and optimized machine-learning models for real-world signals — someone who thrives where algorithms meet real users and who's excited to drive camera-based blood-pressure estimation in digital health.

Do you want to apply your expertise in ML and signal processing to shape a technology that will impact millions of people? Then we're excited to meet you

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