Machine Learning Engineer

Key Responsibilities • Develop, train, and evaluate machine learning models for various applications (e.g., classification, regression, recommendation, NLP). • Implement and experiment with different optimization algorithms (e.g., SGD, Adam, RMSprop) to improve model convergence and performance. • Collaborate with data scientists to translate prototypes into production-ready models. • Conduct hyperparameter tuning and model selection using automated and manual techniques. • Monitor model performance in production and iterate based on feedback and metrics. • Build reusable pipelines for data preprocessing, model training, and deployment. • Stay up-to-date with the latest research in machine learning and optimization techniques. Required Qualifications • Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field. • Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn. • Solid understanding of machine learning algorithms and optimization methods. • Experience with model deployment and serving frameworks (e.g., MLflow, FastAPI, Docker). • Familiarity with cloud platforms (AWS, GCP, Azure) and distributed computing. • Excellent problem-solving skills and attention to detail. Preferred Qualifications • Experience with deep learning architectures (CNNs, RNNs, Transformers). • Knowledge of advanced optimization techniques (e.g., learning rate schedules, gradient clipping, second-order methods). • Contributions to open-source ML projects or published research. • Experience with MLOps tools and practices.