Building intelligent, production-ready systems with expertise in Machine Learning, Deep Learning, Computer Vision, LLMs, RAG Pipelines, and Cloud Deployment.

• 🎓 Computer Science Graduate
• 💼 AI/ML Engineer
• 🤖 Working on RAG Systems, Agentic AI, and Computer Vision
• ☁️ Experienced with GCP, APIs, and Production ML Deployments
• 🎯 Focused on building AI systems that solve real-world problems

• Built and curated high-quality datasets for Machine Learning and Computer Vision applications, including preprocessing, annotation, quality assurance, and validation.
• Designed, trained, and deployed YOLO-based models for object detection and image segmentation, along with CNN-based classification models for structured and unstructured data.
• Developed advanced RAG pipelines and Agentic AI workflows for context-aware LLM applications with multi-step reasoning capabilities.
• Engineered and deployed production-grade ML systems through Flask/FastAPI REST APIs, leveraging Docker and Google Cloud Platform (GCP) for scalable infrastructure.

Python

TensorFlow PyTorch Scikit-learn XGBoost OpenCV Pandas NumPy

• Deep Learning (CNNs, Transformers)
• Computer Vision (YOLO, Image Processing)
• Generative AI (RAG, LLMs, Prompt Engineering)

LangChain LangGraph CrewAI

Flask FastAPI

Google Cloud Platform (GCP) Docker

PostgreSQL MongoDB MySQL Vector Databases

• Building scalable RAG systems and LLM-powered applications
• Exploring Agentic AI workflows and autonomous systems
• Developing real-world Computer Vision solutions

I believe AI is not just about training models — it's about building complete systems that create real-world impact 🚀