We are looking for an experienced Python developer with expertise in machine learning and signal processing to collaborate on developing a heart rhythm subclassification algorithm. Our goal is to further refine ECG rhythm analysis by subclassifying heart rhythms based on specific characteristics using the data we provide. Scope of Work: Develop a subclassification algorithm for heart rhythms using ECG data. Implement machine learning techniques to categorize rhythms into finer subgroups. Work closely with our team to integrate domain-specific logic for classification. Optimize the model for accuracy, precision, and real-time performance. Validate and test the model against labeled ECG datasets. Required Skills & Expertise: Proficiency in Python and relevant ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience in ECG signal processing, time-series analysis, and feature engineering. Strong understanding of classification models, deep learning (CNNs, RNNs, LSTMs). Knowledge of cardiac rhythm characteristics and ECG interpretation is a plus. Experience with data preprocessing, augmentation, and statistical validation. Preferred Qualifications: Prior experience working with medical or physiological datasets. Ability to collaborate and iterate based on medical/clinical feedback. Experience with deploying AI models via APIs or embedded systems.