BPC/BPR
Designed structured workflows and annotation standards to streamline processes - Built and validated blueprint responses ensuring accuracy, quality, and compliance - Collaborated with teams to implement scalable, repeatable ML workflows
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I am a Computer Applications graduate with 2 years of hands-on experience in quality assurance, data validation, and process testing, primarily focused on data labeling and annotation workflows. My background includes conducting systematic QA reviews on large-scale datasets, identifying and documenting errors, and collaborating closely with engineering teams to ensure data integrity and accuracy. I have worked extensively with tools like CVAT and Labelbox, leveraging my skills in Python, SQL, and Excel to validate and optimize annotation pipelines. My experience spans creating detailed test documentation, training team members on quality standards, and leading process improvements that resulted in measurable efficiency gains. With a strong foundation in the software development lifecycle and certifications in AWS and Oracle AI, I am committed to delivering high-quality, reliable training data for machine learning and AI projects.
Designed structured workflows and annotation standards to streamline processes - Built and validated blueprint responses ensuring accuracy, quality, and compliance - Collaborated with teams to implement scalable, repeatable ML workflows
- Labeled facial datasets using CVAT (bounding boxes, segmentation) for recognition models - Performed QA reviews ensuring annotation accuracy
- Labeled facial datasets using CVAT (bounding boxes, segmentation) for recognition models - Performed QA reviews ensuring annotation accuracy
Bachelor of Computer Applications, Computer Applications
Intermediate, General Studies
Analyst AI/ML Practice
Process Associate