Professional Overview
AI evaluation and software engineering professional with an M.S. in Computer Science (AI & ML) from the University of Virginia and over five years of experience evaluating LLM outputs, generating RLHF preference data, and building rubric-based evaluation pipelines. Currently implements MCP tools and expands test coverage for agentic coding assistants, while developing multi-file software projects with deterministic test suites and Docker-based environments. Also brings hands-on computer vision experience, including training YOLOv8/v9 models to 91% [email protected], along with product management and cross-functional roadmap ownership.
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.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
