Chintham M.

Key Skills

Software

Data Annotation Tech

Scale AI

Mindrift

Top Subject Matter

Autonomous Vehicles & Robotics

Healthcare & Medical AI

Conversational AI & Customer Suppor

Top Data Types

Document

Top Task Types

Fine-tuning

Freelancer Overview

With over two years of hands-on experience in data labeling and AI training data preparation, I have contributed to projects across computer vision, NLP, and speech recognition domains. My key skills include precise bounding box annotation, polygonal segmentation, sentiment and intent labeling, and audio transcription with timestamps. I have worked on high-stakes datasets for autonomous vehicle perception (e.g., labeling pedestrians, traffic signs in varied conditions) and conversational AI (e.g., intent classification, entity tagging for customer support chatbots). What sets me apart is my ability to maintain 98%+ inter-annotator agreement, create and refine annotation guidelines to reduce ambiguity, and use Python scripts (Pandas, OpenCV) for basic quality checks and preprocessing. I am also experienced in tools like Labelbox, CVAT, and Prodigy, and I’ve mentored junior labelers to improve consistency and throughput.* *Additionally, I’ve led a project to semi-automate label verification for medical imaging data, reducing rework by 30% while ensuring compliance with privacy standards. My attention to detail, fast learning of new ontologies, and feedback-driven approach to edge-case handling have consistently improved model performance in production. I am eager to apply these skills to help build robust, bias-aware training datasets that accelerate AI development

Education

Work History