Data Annotation
I worked on object detection projects where I created bounding boxes around objects in images and performed data labeling and annotation to build high-quality training datasets for Deep learning models.
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With over three years of experience in AI and data science, I specialize in building and optimizing end-to-end machine learning pipelines with a strong focus on high-quality data labeling, annotation, and AI training data. I have worked extensively on NLP projects such as LLM fine-tuning, sentiment analysis, and prompt evaluation, as well as computer vision tasks like real-time object detection and tracking using YOLO and CNNs. My hands-on expertise includes Python, TensorFlow, PyTorch, Hugging Face, LangChain, LlamaIndex, and Azure, and I have a proven track record of ensuring data quality and compliance through prompt analysis and content moderation for AI safety. I enjoy collaborating with teams to design data-centric solutions that drive model accuracy and responsible AI development.
I worked on object detection projects where I created bounding boxes around objects in images and performed data labeling and annotation to build high-quality training datasets for Deep learning models.
Master of Computer Applications, Computer Applications
Bachelor of Computer Applications, Computer Applications
AI/ML Engineer
Data Scientist