For our client we are looking for a highly skilled Machine Learning. The person in this role will be responsible for developing and optimizing ML models for analyzing data from breath sensor devices, working with time-series data, and applying signal processing techniques in clinical trials.

Machine Learning Engineer

Your responsibilities

• Develop and optimize machine learning models for binary and multi-class classification in clinical trials.
• Work with time-series sensor data from Breath analyzer sensor devices.
• Apply signal processing techniques to denoise and preprocess sensor traces.
• Optimize models for different metrics such as accuracy, sensitivity and specificity.
• Contribute to the automation of data ingestion and processing.
• Collaborate with data engineers, software developers, and clinical researchers to integrate machine learning models into clinical workflows.
• Document methodologies and results for regulatory and investor presentations.

Our requirements

• Academic degree in Machine Learning, Data Science, Electrical Engineering, Physics, or a related field.
• Strong Python skills, with experience in Scikit-Learn, TensorFlow, PyTorch, or equivalent ML frameworks.
• Expertise in signal processing and time-series analysis.
• Knowledge of feature engineering and statistical analysis.
• Strong understanding of model validation techniques.
• Experience with C# (for application support).
• Experience in medical device AI development.
• Familiarity with clinical trial data management and regulatory requirements.
• Background in biomedical signal processing or sensor fusion algorithms.