Artificial Intelligence And Machine Learning Consultant

Roles and Responsibilities

• Design, develop, train, and deploy machine learning models using Python and AWS services.
• Build end-to-end machine learning pipelines for data preprocessing, feature engineering, model training, and inference.
• Use Amazon SageMaker for model development, training, deployment, and monitoring.
• Develop and implement machine learning algorithms for classification, regression, clustering, and prediction.
• Perform exploratory data analysis, data cleaning, and feature engineering using Python libraries.
• Work with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch, depending on project requirements.
• Integrate ML models with applications and backend services using APIs.
• Implement model evaluation, hyperparameter tuning, and performance optimization.
• Deploy scalable inference solutions using AWS SageMaker endpoints, AWS Lambda, or container-based services.
• Monitor model performance, data drift, and model accuracy in production.
• Collaborate with data engineers, software developers, and business stakeholders to translate business requirements into AI/ML solutions.
• Follow best practices for model versioning, reproducibility, security, and deployment automation.
• Document model development processes, experiments, and deployment workflows.

Must-Have Skills

• Strong programming experience in Python.
• Good understanding of machine learning algorithms and statistical concepts.
• Hands-on experience with data preprocessing, feature engineering, model training, and evaluation.
• Experience with Scikit-learn and at least one deep learning framework, such as TensorFlow or PyTorch, where required by the project.
• Hands-on experience with AWS services, preferably Amazon SageMaker.
• Knowledge of AWS S3 for storing datasets, model artifacts, and training outputs.
• Experience deploying and integrating ML models into applications.
• Strong understanding of model evaluation metrics and performance optimization.
• Good SQL skills and experience working with structured datasets.
• Understanding of REST APIs and basic software development practices.