We are looking for a highly skilled and motivated Machine Learning Engineer with a strong background in the processing, analysis, and modeling of biomedical signals - preferably time-series data using Python. In this role, you will contribute to the development and optimization of data pipelines and signal processing algorithms for cutting-edge medical devices.
The ideal candidate has hands-on experience working with physiological signals such as bioimpedance, PPG, ECG, EMG, or EEG, and demonstrates a solid understanding of signal analysis and machine learning techniques. A passion for translating scientific knowledge into real-world clinical applications is essential.
responsibilities :
Process, analyze, and model biomedical signals and data, including tasks such as filtering, denoising, segmentation, feature extraction, classification, and the development and validation of predictive models.
Write clean, maintainable Python code, create appropriate documentation, and manage source code using version control systems (e.g., GitLab).
Research and evaluate advanced methods and algorithms used in biomedical signal processing, with a focus on their practical application and effectiveness.
Optimize existing data pipelines, models, and signal processing algorithms to improve efficiency, accuracy, and scalability.
Leverage AI technologies, including large language models (LLMs), to enhance productivity and support engineering workflows.
Collaborate within a multidisciplinary team of engineers, clinicians, and researchers to drive innovation in medical device development.
Stay up-to-date with the latest developments in biomedical signal processing, machine learning, and artificial intelligence by reviewing current scientific literature and relevant publications.
requirements-expected :
M.Sc. degree in Biomedical Engineering, Medical Physics, Computer Science, Neuroscience, or a related field.
Minimum 2 years of hands-on experience in biomedical signal processing, analysis, and modeling.
Strong understanding of mathematical, statistical, and algorithmic concepts relevant to machine learning and biomedical signal analysis.
Proficiency in Python programming, including experience with scientific computing and data processing libraries (e.g., NumPy, SciPy, pandas, scikit-learn). Excellent problem-solving skills and the ability to work effectively in a collaborative, dynamic multidisciplinary environment.
Strong communication skills to present technical concepts to both technical and non-technical stakeholders.
offered :
Opportunity to work on the full lifecycle of innovative medical technologies — from concept and prototyping to final product development.
Key role within a multidisciplinary development team, with real influence on the direction and outcomes of the project.
Dynamic, growth-oriented environment, ideal for ambitious professionals seeking career advancement and skill development.
Exposure to an international and collaborative culture, working alongside experts across engineering, science, and clinical domains.
A comprehensive benefits package, including standard employment perks and flexible work conditions.
