Professional Overview
Computer Science undergraduate with experience in RLHF, AI model evaluation, prompt engineering, response ranking, data annotation, QA, Python, SQL, Git, computer vision, and ML. Skilled in guideline-based evaluation, accuracy validation, and high-quality AI training data creation.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Worked on the AI voice vendor for easy customer interaction and navigation
- Trained a model from scratch with my own voice as audio samples using Audacity
- Tested the model on Coqui TTS
- Learnt Audio Engineering, Sampling Techniques, Noise Reduction, Colab datasets
Key Achievements / KPIs
- Built and deployed AI vendor - the voice assistant
- A complete production-level LLM chatbots as a version 1
Education
Field of Study: Computer Science Engineering
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.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
