I am a professional Data Annotation Specialist with over one year of focused experience supporting projects in Artificial Intelligence, Machine Learning, Deep Learning, and Natural Language Processing. My work centers on creating accurate, well-structured, and reliable training datasets that help startups, researchers, and established companies improve model performance and achieve better results in real-world applications.

I bring more than five years of hands-on experience working with AI datasets, ensuring high precision and strict quality control throughout every stage of annotation. I am skilled in preparing data in multiple industry-standard formats, including YOLO, COCO, Pascal VOC, JSON, XML, and CSV, which allows smooth integration into different machine learning pipelines. I am also experienced with popular annotation tools such as LabelImg, CVAT, VGG Image Annotator, and Supervisely, enabling efficient handling of large-scale projects.

I have contributed to projects across diverse industries, including autonomous vehicles, medical AI, e-commerce and retail, surveillance and security, NLP chatbot development, and computer vision systems. My strengths include fast turnaround times, clear communication, and a strong commitment to confidentiality through NDA compliance and secure data handling practices.

Overall, my goal is to deliver clean, consistent, and high-quality annotated datasets that help AI models learn faster, perform better, and deliver meaningful business value.