Key Responsibilities: - Design and implement Machine Learning pipelines for classification, regression, and clustering. - Perform data preprocessing, feature engineering, and analysis of datasets. - Optimize model performance. - Document the workflows, processes, and technical decisions. Requirements: - Experience in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch. - Understanding of supervised and unsupervised learning methods. - Proficient in data manipulation tools (Pandas and NumPy). - Knowledge of model evaluation metrics and validation techniques. - Experience in time-series, transactional, text and image data. - Strong problem-solving skills and the ability to work independently. Preferred Skills: - Understanding of ethical AI practices and data privacy regulations. - Familiarity with Git and collaborative development. - Strong communication skills to collaborate with cross-functional teams. Mandatory Skills: Python, scikit-learn, pandas, Git.