Multilingual Text Annotation & Translation for AI Language Models
Worked on multilingual AI data labeling and annotation projects involving Punjabi, Hindi, and English content for training and improving language models. Responsibilities included annotating and classifying text data, performing Named Entity Recognition (NER), validating AI-generated responses, emotion tagging, and evaluating linguistic accuracy. Handled translation and localization tasks to ensure culturally accurate and context-aware datasets for NLP systems. Contributed to prompt–response writing and supervised fine-tuning (SFT) by creating and reviewing human-like responses for LLM training. The project required high attention to detail, strong grammatical knowledge, and consistency across large datasets. Maintained quality standards while meeting strict deadlines and collaborated with remote teams to improve dataset reliability and performance. This work directly supported the development of more accurate, inclusive, and human-aligned AI language models.