Machine Learning Engineer at Si-Ware Systems | Cairo

Key Responsibilities:Conduct data cleaning, preprocessing, and transformation to prepare datasets for training and evaluation. Contribute to the design, training, and enhancement of machine learning models. Plan and carry out structured experiments utilizing validation strategies such as cross-validation, hold-out testing, and statistical comparison. Assess model performance with metrics like Accuracy, Precision, Recall, F1 Score, and RMSE. Optimize models and inference pipelines to meet performance, memory efficiency, and real-time constraints. Ensure reproducibility, traceability, and validation of models in regulated or industrial settings. Support chemometrics workflows including spectral preprocessing, feature extraction, multivariate modeling, and validation for spectroscopy applications. Production & System Integration:Develop and implement production-ready ML pipelines integrated with software and hardware systems. Ensure that models are maintainable, version-controlled, and deployable within real-world applications. Contribute to the design and evolution of ML system architecture and reusable pipeline components. Create unit and integration tests for ML components.