I’m an AI Evaluator and Data Annotation Specialist with 1+ years of hands-on experience in high-quality dataset creation, LLM evaluation, and AI output validation across NLP and multimodal workflows. I have strong expertise in prompt engineering (zero-shot, few-shot, CoT), RLHF evaluation, and hallucination detection, with a track record of improving model accuracy through structured feedback.
I am proficient in Python, SQL, REST APIs, and building data pipelines, and I regularly work with OpenAI API, Hugging Face, LangChain, and SageMaker. I have hands-on experience with annotation platforms such as Label Studio, CVAT, Labelbox, Prodigy, Roboflow, AWS SageMaker, and Azure ML, and I thrive in Agile environments, managing annotation tasks at scale to deliver audit-ready datasets under tight deadlines.
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