Professional Overview
I am a Computer Engineering graduate with a strong focus on Artificial Intelligence, Machine Learning, Generative AI, and LLM-based applications. I have hands-on experience with Python, PyTorch, LangChain, LangGraph, RAG, vector databases, LLM APIs, and AI agent architectures. I enjoy building end-to-end AI systems, from data processing and model development to agent orchestration and API integration. I have worked on projects involving stock prediction and sentiment analysis, retrieval-augmented generation, multi-step AI agents, tool calling, state management, and evaluation workflows. My current focus is on building reliable and production-oriented AI systems using modern agentic architectures. I am particularly interested in AI/ML Engineer, Generative AI Engineer, LLM Engineer, and AI Agent Engineer roles where I can contribute to real-world AI products while continuously improving my engineering and machine-learning skills.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.