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I am Julius Mutua, a detail-oriented Data Annotator and Image Rater with hands-on experience supporting AI and machine learning projects through accurate image labeling, categorization, and quality review. I excel at applying annotation guidelines, performing pixel-level and bounding box labeling, and ensuring high annotation accuracy across large datasets. I am adept at remote collaboration, interpreting guidelines, and maintaining productivity and quality metrics while meeting strict deadlines.…I am Julius Mutua, a detail-oriented Data Annotator and Image Rater with hands-on experience supporting AI and machine learning projects through accurate image labeling, categorization, and quality review. I excel at applying annotation guidelines, performing pixel-level and bounding box labeling, and ensuring high annotation accuracy across large datasets. I am adept at remote collaboration, interpreting guidelines, and maintaining productivity and quality metrics while meeting strict deadlines.

Julius Mutua

Data Annotator, Data Analyst, Data Scientist, +2

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I am Julius Mutua, a detail-oriented Data Annotator and Image Rater with hands-on experience supporting AI and machine learning projects through accurate image labeling, categorization, and quality review. I excel at applying annotation guidelines, performing pixel-level and bounding box labeling, and ensuring high annotation accuracy across large datasets. I am adept at remote collaboration, interpreting guidelines, and maintaining productivity and quality metrics while meeting strict deadlines.…I am Julius Mutua, a detail-oriented Data Annotator and Image Rater with hands-on experience supporting AI and machine learning projects through accurate image labeling, categorization, and quality review. I excel at applying annotation guidelines, performing pixel-level and bounding box labeling, and ensuring high annotation accuracy across large datasets. I am adept at remote collaboration, interpreting guidelines, and maintaining productivity and quality metrics while meeting strict deadlines.

Available to hire

I am Julius Mutua, a detail-oriented Data Annotator and Image Rater with hands-on experience supporting AI and machine learning projects through accurate image labeling, categorization, and quality review. I excel at applying annotation guidelines, performing pixel-level and bounding box labeling, and ensuring high annotation accuracy across large datasets. I am adept at remote collaboration, interpreting guidelines, and maintaining productivity and quality metrics while meeting strict deadlines.

Skills

Experience Level

Expert

Expert

Intermediate

Intermediate

Intermediate

Work Experience

Data Annotator at Samasource

February 1, 2023 - Present

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.

July 1, 2024 - September 1, 2025

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.