Seasoned AI/ML Engineer with over 5 years of experience in designing, developing, and deploying scalable AI-driven applications and machine learning solutions.Proficient in utilizing Python frameworks such as TensorFlow, PyTorch, and Flask to build maintainable, efficient machine learning models and AI systems that meet project requirements and exceed client expectations.Skilled in leveraging machine learning libraries like NumPy, Pandas, and Matplotlib for data analysis, model training, and visualization, enabling data-driven decision-making and insights.Implemented RESTful APIs for seamless integration of machine learning models, enabling efficient interaction between AI services and distributed components.Proficient in designing, implementing, and optimizing data architectures for machine learning pipelines, utilizing both SQL and NoSQL databases to handle diverse data models and large-scale datasets.Experienced in front-end development technologies including HTML, CSS, and JavaScript for building interactive AI-based applications, with expertise in consuming data in XML and JSON formats for seamless communication with back-end systems.Deployed AI models and scalable applications on AWS, leveraging services such as EC2, Lambda for serverless model inference, S3 for data storage, and SNS for notifications.Developed automated test suites for machine learning workflows using pytest and unittest, ensuring code quality, reliability, and accuracy in predictions.Orchestrated containerized machine learning applications on Kubernetes, managing model deployment, scaling, and monitoring for high availability and performance in production environments.Implemented monitoring solutions using tools like Prometheus, Grafana, or ELK stack to track model performance, detect anomalies, and troubleshoot issues in AI applications.Leveraged infrastructure as code (IaC) tools like Terraform and CloudFormation to automate cloud resource provisioning for scalable machine learning deployments and CI/CD pipelines.Implemented secure authentication mechanisms in AI systems using JWT and OAuth 2.0, ensuring secure access to sensitive data and seamless integration with third-party services.Developed distributed data processing applications with PySpark, handling large datasets and applying machine learning algorithms for scalable data analysis and predictions.