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.