LLM Sandbox Authoring
Evaluation of LLM prompt and response over specific criteria like harmfulness, truthfulness etc
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I have nearly three years of experience working in data labeling and AI training data, primarily focusing on creating high-quality labeled datasets for machine learning models. My expertise includes annotating text, image, and audio data, ensuring accuracy, consistency, and adherence to project guidelines. I am skilled in using tools such as Labelbox and Supervisely, and have collaborated closely with data scientists to optimize dataset quality for model training and evaluation. During my experience, I’ve contributed to projects across various industries, including natural language processing (NLP), image recognition, and sentiment analysis. I am detail-oriented and proficient at spotting nuances in data, which ensures that training datasets are reliable and robust for AI model development. My strong communication skills and collaborative approach also allow me to work effectively with cross-functional teams, ensuring that project goals are met on time and with precision.
Evaluation of LLM prompt and response over specific criteria like harmfulness, truthfulness etc
Evaluation of LLM prompt and response over specific criteria like harmfulness, truthfulness etc
Evaluation of LLM prompt and response over specific criterias like harmfulness, truthfulness etc
Post Graduate Degree, Data Analytics & Machine Learning
Bachelor of Science, Chemical Engineering
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