Skills
Artificial Intelligence & Machine Learning:
✔ Generative AI | Large Language Models (LLMs) | Retrieval-Augmented Generation (RAG) | Fine-Tuning & Prompt Engineering | Deep Learning | Supervised & Unsupervised Learning | AI Agents
Programming & Frameworks:
✔ Python | Java | C | SQL | TensorFlow | PyTorch | OpenVINO | Hugging Face Transformers | LangChain | AutoGen | FastAPI
Data Science & NLP:
✔ Natural Language Processing (NLP) | Named Entity Recognition (NER) | Sentiment Analysis | Tokenization | Vector Embeddings | Text Summarization | Chatbot Development
Computer Vision & Image Processing:
✔ OpenCV | Dlib | CNNs | ResNet | Vision Transformers (ViTs) | Object Detection (YOLO, Faster R-CNN) | Image Segmentation | Medical Image Analysis
Search & Retrieval Systems:
✔ FAISS | Pinecone | Qdrant | ElasticSearch | Semantic Search | Knowledge Graphs
Cloud & MLOps:
✔ AWS (S3, Lambda, SageMaker) | Google Cloud | Azure AI | Kubernetes | Docker | CI/CD | Model Deployment | API Development
Big Data & Databases:
✔ PostgreSQL | MongoDB | Redis | Apache Kafka | Hadoop | Spark
Productivity & Collaboration Tools:
✔ Microsoft Excel | Microsoft Word | Google Analytics | JIRA | Trello | Notion | Git | GitHub | Confluence
About
Results-driven AI/ML Engineer with hands-on experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents. Proficient in developing deep learning models, computer vision systems, and NLP-based solutions, with expertise in frameworks like TensorFlow, PyTorch, LangChain, OpenVINO, and Hugging Face Transformers.
Successfully built MediQuery AI, a multimodal medical assistant integrating vision transformers and transformer-based NLP for advanced healthcare diagnostics. Developed an AI-powered workflow automation system, reducing manual processing time by 60%.
Skilled in vector search (FAISS, Pinecone, Qdrant), cloud computing (AWS, GCP), and MLOps, optimizing AI model performance and deployment. Strong problem-solving abilities with a track record of increasing AI system efficiency by up to 40%.
Recipient of Amazon ML Summer School 2023 recognition (Top 3000) and a three-time government scholarship awardee. Passionate about cutting-edge AI research, innovation, and real-world AI applications.
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