Machine Learning Engineer | AWS re/Start Certified | Tensorflow, PyTorch, Python, Django, NLP, CV

I am a results-driven Machine Learning and Backend Engineer with a deep curiosity for understanding and engineering complex systems. With a strong foundation in Data Structures, Algorithms, and distributed computing, I thrive on solving challenging problems and building scalable, high-performance solutions.

My expertise spans machine learning, NLP, and Retrieval-Augmented Generation (RAG)-based systems, alongside backend development using Python (Django, FastAPI) and Node.js. I have hands-on experience with PostgreSQL, MongoDB, and Redis for efficient data storage, as well as cloud technologies like AWS (Lambda, S3, EC2) and Docker to deploy robust applications. I am well-versed in designing distributed systems, optimizing API performance, and implementing CI/CD pipelines for streamlined development workflows.

I have successfully led the development of an AI-powered exam grading system GradeMate, improving grading efficiency by 85% through NLP and RAG techniques. Additionally, I have built scalable backend APIs for real-time data processing, reducing response times by 70%, and optimized database queries and caching strategies to enhance application performance by 90%. With a strong problem-solving mindset and experience collaborating in cross-functional teams, I am committed to delivering impactful solutions.

I am currently seeking opportunities as a Machine Learning Engineer, Backend Engineer, or Software Engineer in teams focused on AI-driven applications, scalable architectures, and data-intensive solutions. Passionate about innovation and continuous learning, I aim to contribute my expertise in a dynamic, high-impact environment.