Machine Learning Engineer with 7+ years experience

Contribute significantly to the architectural decisions for our ML platform and applications\n.Data Engineering for ML : Design and implement data pipelines for feature engineering, data transformation, and data versioning to support ML model training and inference\n.MLOps & Productionization : Establish and implement best practices for MLOps, including CI/CD for ML, automated testing, model versioning, monitoring (performance, drift, bias), and alerting systems for production ML models\n.Performance & Scalability : Identify and resolve performance bottlenecks in ML systems. Ensure the scalability and reliability of deployed models under varying load conditions\n.Documentation : Create clear and comprehensive documentation for ML models, pipelines, and services\n.Good to have Machine Learning Expertise\n:Solid theoretical and practical understanding of various machine learning algorithm\nsProficiency with ML frameworks such as PyTorch, Scikit-learn\n.Experience with feature engineering, model evaluation metrics, and hyperparameter tunin\n\ng