I'm a passionate Data scientist with a strong foundation in Software engineering, machine learning and cloud. I leverage my expertise in cloud platforms like AWS and Google Cloud to design, develop, and deploy scalable and reliable systems.My experience encompasses the entire machine learning pipeline, from grasping fundamentals to model development and deployment using tools like MLflow and SageMaker. I also implement DevOps practices with CI/CD pipelines and containerization using Docker to ensure efficient workflows.Here are some examples of how I've applied my skills:Fine-tuned a large language model (LLM) for financial data: I used AWS SageMaker to adapt the Meta Llama2-7b model for understanding and generating financial text, showcasing my ability to leverage cutting-edge NLP techniques.Built a web application for census prediction: I transformed a model from Jupyter Notebook to a full-fledged web app deployed on AWS Lambda, utilizing FastAPI and Pydantic for robustness and scalability.Developed an image classifier: I leveraged PyTorch and pre-trained CNN models to create an image classification system.Microservice architecture with AWS: I built a user activity microservice using AWS, Flask, and Kubernetes to provide business analysts with data.Containerized web application: I deployed a highly available and secure Nginx web application using CloudFormation and Infrastructure as Code (IaC) principles.I'm a collaborative learner who thrives in fast-paced environments. I'm constantly seeking opportunities to expand my knowledge and contribute to innovative projects that make a real impact.
