Professional Overview
I’m a Computer Science student focused on AI and backend systems, with hands-on experience building production-style AI applications. I’m comfortable with Python (async, type hints, modern patterns) and have used TypeScript in full-stack projects. I’ve also worked with containerized environments using Docker and understand how to structure services
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.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.