I’m an AI Trainer and Data Annotation Specialist with hands-on experience in training, evaluating, and improving large AI models across text, image, video, and audio modalities. My work focuses on creating high-quality datasets that drive accuracy, safety, and fairness in AI systems. Recently, I’ve specialized in audio quality annotation identifying and classifying distortions, noise, and clarity issues in sound samples to help AI models better understand and generate human-like audio. My cross-domain experience from medical data to speech analysis enables me to bring precision, pattern recognition, and quality control to every dataset I handle. Core Competencies: 🎧 Audio Quality Assessment & Annotation 🧠 Prompt Engineering & AI Model Evaluation 📊 Data Cleaning, Labeling & Quality Control 🧩 Machine Learning (SFT, RLHF, Generative AI) 💬 Communication & Cross-Functional Collaboration I’m passionate about contributing to next-generation AI systems that learn safely and perform reliably in real-world applications. Always eager to collaborate with teams building cutting-edge solutions in audio AI, data science, and machine learning.
