Machine Learning Specialist

Role Overview: You will be responsible for writing clean, efficient, and well-documented Python code adhering to OOP principles such as encapsulation, inheritance, polymorphism, and abstraction. Your role will involve working with Python and related libraries like TensorFlow, PyTorch, and Scikit-Learn. Your main responsibility will be managing the entire ML pipeline from data ingestion and preprocessing to model training, evaluation, and deployment. Key Responsibilities: - Design, develop, and deploy machine learning models and intelligent systems into production environments, ensuring they are robust, scalable, and performant. - Apply strong software engineering principles to design and build clean, modular, testable, and maintainable ML pipelines, APIs, and services. - Contribute significantly to the architectural decisions for the ML platform and applications. - Design and implement data pipelines for feature engineering, data transformation, and data versioning to support ML model training and inference. - 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. Qualifications Required: - Experience in writing Python code and working with libraries like TensorFlow, PyTorch, and Scikit-Learn. - Strong understanding of OOP principles (encapsulation, inheritance, polymorphism, abstraction). - Knowledge of data engineering for ML, software design & architecture, and MLOps practices would be preferred.,