Professional Overview
I build and deploy production-oriented AI and backend systems using Python, RAG, LLMs, hybrid retrieval, semantic search, BM25, embeddings, cross-encoder reranking, FastAPI, Docker, CI/CD, and cloud infrastructure. I can design document ingestion and indexing pipelines, build reliable APIs, implement evaluation and security, and turn AI concepts into practical, usable applications.
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.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
