Professional Overview
Applied AI Engineer with 5+ years of experience at Microsoft building and evaluating enterprise NLP and LLM systems. Currently, provide AI, data science, and math expertise across independent engagements, supporting LLM training, AI engineering and model improvement for frontier AI labs and AI organizations. Bachelor’s degree in Math and Computing.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built and evaluated agentic AI systems for security and compliance
- Implemented a synthetic task generation pipeline for RL Fine-Tuning (security)
- Led development of NLP classifiers to detect offensive workplace communication
Key Achievements / KPIs
- Evaluation framework for 10+ security scenarios, covering 8 eval dimensions
- Cut hallucinated tasks by 30–40% and increased complex tasks by 45%
- Achieved 29% reduction in FPs (at fixed recall) for business conduct classifiers
Education
Field of Study: Mathematics and Scientific Computing
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.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
