Machine Learning Engineer
Current• Developed and implemented machine learning algorithms for various applications, including natural language processing, computer vision, and predictive analytics.• Conducted data preprocessing, feature engineering, and model training using Python, TensorFlow, and scikit-learn.• Collaborated with cross-functional teams to integrate machine learning models into production systems and optimize performance.• Contributed to research and development projects, staying abreast of the latest advancements in machine learning technologies.• Developed and implemented deep learning frameworks like TensorFlow, PyTorch, and Keras. • Involved in design, implement, and optimize deep neural networks for tasks such as image recognition, natural language processing, and time series analysis.• Conducted exploratory data analysis using libraries like NumPy, Pandas, and SciPy. • Familiar with techniques such as normalization, scaling, dimensionality reduction, and outlier detection.• Conducted evaluating and validating machine learning models using appropriate metrics and techniques. And perform cross-validation, hyper parameter tuning, and model selection to ensure robust and generalizable performance.
