AI Data Analyst & Quality Assurance (Computer Vision) (Project D)
QA Specialist - AI Data Annotation Quality Control: Conducted rigorous audits of annotated datasets (text, image, or video) to ensure 100% alignment with project guidelines. Error Analysis: Identified patterns of mislabeling and provided detailed feedback reports to improve the accuracy of the annotation team. Guideline Refinement: Collaborated with Data Scientists to clarify edge cases and update annotation manuals for better consistency. Data Validation: Verified the 'Ground Truth' for complex AI projects, ensuring the models are trained on unbiased, high-quality information. Quality Assurance & Auditing: Promoted to a QA Auditor role within the first 3 months due to consistent top-tier performance. Responsible for validating the accuracy and logic of large-scale datasets used for training Generative AI models (RLHF). Generative AI Data Creation: Specialized in creating complex, multimodal synthetic data (Text-to-Image). Developed high-fidelity conversational scenarios with lon