AI/ML Research Intern – Data Annotation and Bias Auditing
TextEntity Ner Classification
As an AI/ML Research Intern, I preprocessed and annotated over 100K multilingual text samples for large language model (LLM) training. I applied active learning strategies to enhance dataset quality and reduce labeling errors by 25%. Additionally, I conducted bias audits using fairness libraries to document mitigation approaches for disparity reduction.
• Labeled and annotated multilingual textual data for supervised machine learning models.
• Leveraged active learning methods to iteratively improve model performance and annotation quality.
• Performed bias audits and contributed to dataset debiasing initiatives in NLP pipelines.
• Collaborated with research teams to publish findings and maintain data integrity.
As an AI/ML Research Intern, I preprocessed and annotated over 100K multilingual text samples for large language model (LLM) training. I applied active learning strategies to enhance dataset quality and reduce labeling errors by 25%. Additionally, I conducted bias audits using fairness libraries to document mitigation approaches for disparity reduction. • Labeled and annotated multilingual textual data for supervised machine learning models. • Leveraged active learning methods to iteratively improve model performance and annotation quality. • Performed bias audits and contributed to dataset debiasing initiatives in NLP pipelines. • Collaborated with research teams to publish findings and maintain data integrity.
2024 - 2024