Julius Mutua
Data Annotation and Labelling
Hire this person
Send a job offer directly to this candidate
About
Detail-oriented Data Annotator and Image Rater with experience supporting AI and machine learning projects through accurate image labeling, categorization, and quality review. Skilled in applying annotation guidelines, performing pixel-level and bounding box labeling, and maintaining high annotation accuracy across large datasets. Experienced in quality assurance, guideline interpretation, and dataset validation for computer vision projects.
Adept at working in remote environments and meeting strict quality and productivity metrics.
Experience
Data Annotator at Samasource (2023-02 – Present)
Annotate and label large-scale image datasets used for training computer vision and machine learning models.
- Annotate and label large-scale image datasets used for training computer vision and machine learning models.
- Apply detailed annotation guidelines and labeling rubrics to identify objects, attributes, and visual patterns within images.
- Perform bounding box, segmentation, and classification annotations according to project requirements.
- Identify annotation inconsistencies and escalate edge cases or unclear images for guideline clarification.
- Support dataset validation by reviewing flagged items and correcting labeling errors.
- Maintain productivity and accuracy metrics while completing high-volume annotation tasks.
Data Annotator at Sapien Corp. (2024-07 – 2025-09)
Performed image annotation and rating tasks to support machine learning datasets for computer vision applications.
- Performed image annotation and rating tasks to support machine learning datasets for computer vision applications.
- Classified and tagged images based on visual content, object presence, and contextual attributes.
- Applied annotation tools to perform object detection labeling, bounding box annotation, and image categorization.
- Reviewed and validated annotated images to ensure consistency with project guidelines and quality benchmarks.
- Documented annotation issues and edge cases to support guideline improvements.
- Maintained high accuracy scores and productivity standards in a remote, task-based annotation environment.
- Followed strict data privacy and confidentiality requirements when handling sensitive datasets.
- Collaborated with QA reviewers to resolve labeling discrepancies and improve annotation consistency.
Education
Bachelor of Business Information Technology in BBIT – Technical University of Kenya
