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Data Annotation Tech
Scale AI
TolokaNo subject matter listed
Computer Code Programming
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TextI am an AI Data Labeling and LLM Evaluation Specialist with a strong foundation in Computer Science and hands-on experience in software development. My background includes extensive work with data-driven applications and AI-powered tools, which has strengthened my analytical reasoning, attention to detail, and understanding of model behavior. I am skilled in evaluating large language model outputs, writing and refining prompts, and assessing response quality across tasks such as question answering, summarization, and text generation. I have worked with data labeling platforms such as Label Studio, Scale AI, and Toloka, focusing primarily on text-based tasks, code evaluation, and instruction-following data. My technical expertise in languages like Python, C++, and JavaScript helps me approach AI evaluation from both a linguistic and logical perspective. I bring precision, consistency, and curiosity to every annotation task, aiming to enhance AI performance and contribute meaningfully to high-quality model training initiatives.
In this project we have to compare the 4 responses generated by the LLM model and select the best response out of them and also tell the reason for selecting that option.
Generate two code responses by giving a prompt to the model then evaluate both of them and select the best out of the two with proper reasoning.
We have to generate two responses by giving a prompt to the model then evaluate the best responses out of the two and select why we selected that.
Bachelor of Technology, Computer Science and Engineering
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Full Stack Web Developer Intern
