Professional Overview
Computer Engineering graduate with strong academic performance (CGPA 3.80), hands-on experience designing and deploying AI systems that solve practical problems. Strong foundation in Python, machine learning, LangChain, GPT-4, RAG pipelines, and backend development with experience delivering real-world solutions. Published research in AI-powered security systems in MDPI's Journal of IoT. Recognized for rapid learning, cross-functional collaboration, and delivering production-ready AI solutions
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.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI Business, Marketing & Strategy
Apply AI to marketing automation, content generation, customer segmentation, and revenue growth strategies.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
