Professional Overview
AI/ML graduate with experience in LLM optimization and audio annotation. Skilled in reducing Word Error Rate, multi-speaker labeling, and sentiment tagging using Label Studio. Proficient in Python, SQL and Django for building NLP and CV apps. Detail-oriented and ready for remote data validation and prompt alignment roles.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Engineered datasets in Label Studio for LLM optimization.
- Reduced Word Error Rate to maximize model accuracy.
- Refined multi-speaker labeling and phonetic audio precision.
- Conducted sentiment analysis and paragraph tagging for NLU.
- Identified non-speech sounds to enrich dataset context.
Key Achievements / KPIs
- Maintained 99% accuracy in audio data validation.
- Consistently delivered high-volume daily annotation output.
- Reduced Word Error Rates for speech models.
Education
Field of Study: Artificial Intelligence and Machine Learning
Areas of Expertise
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.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
