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I’m Purity Wanjiru Pwanjiru, an image annotation specialist with 4 years of experience in computer vision data labeling. I focus on creating high-quality training data for AI/ML models, including bounding boxes, polygons, semantic/instance segmentations, and keypoint annotations. I’ve worked with large image datasets and consistently run quality assurance checks such as multiple review rounds and cross-checking to ensure label accuracy. I also collaborate with data science and ML teams to align annotation guidelines with project goals, improve dataset consistency, and support smooth integration of labeled data into machine learning pipelines.…I’m Purity Wanjiru Pwanjiru, an image annotation specialist with 4 years of experience in computer vision data labeling. I focus on creating high-quality training data for AI/ML models, including bounding boxes, polygons, semantic/instance segmentations, and keypoint annotations. I’ve worked with large image datasets and consistently run quality assurance checks such as multiple review rounds and cross-checking to ensure label accuracy. I also collaborate with data science and ML teams to align annotation guidelines with project goals, improve dataset consistency, and support smooth integration of labeled data into machine learning pipelines.

Purity Wanjiru

Data Annotator, Data Collector, QA Engineer, +2

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I’m Purity Wanjiru Pwanjiru, an image annotation specialist with 4 years of experience in computer vision data labeling. I focus on creating high-quality training data for AI/ML models, including bounding boxes, polygons, semantic/instance segmentations, and keypoint annotations. I’ve worked with large image datasets and consistently run quality assurance checks such as multiple review rounds and cross-checking to ensure label accuracy. I also collaborate with data science and ML teams to align annotation guidelines with project goals, improve dataset consistency, and support smooth integration of labeled data into machine learning pipelines.…I’m Purity Wanjiru Pwanjiru, an image annotation specialist with 4 years of experience in computer vision data labeling. I focus on creating high-quality training data for AI/ML models, including bounding boxes, polygons, semantic/instance segmentations, and keypoint annotations. I’ve worked with large image datasets and consistently run quality assurance checks such as multiple review rounds and cross-checking to ensure label accuracy. I also collaborate with data science and ML teams to align annotation guidelines with project goals, improve dataset consistency, and support smooth integration of labeled data into machine learning pipelines.

Available to hire

I’m Purity Wanjiru Pwanjiru, an image annotation specialist with 4 years of experience in computer vision data labeling. I focus on creating high-quality training data for AI/ML models, including bounding boxes, polygons, semantic/instance segmentations, and keypoint annotations.

I’ve worked with large image datasets and consistently run quality assurance checks such as multiple review rounds and cross-checking to ensure label accuracy. I also collaborate with data science and ML teams to align annotation guidelines with project goals, improve dataset consistency, and support smooth integration of labeled data into machine learning pipelines.

Skills

Experience Level

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Data Annotation Associate at Mindrift

January 1, 2024 - January 1, 2025

Annotated diverse computer vision datasets for applications including autonomous driving, healthcare imaging, and retail AI. Followed strict labeling protocols to maintain consistency across large teams and flagged ambiguous images for review. Assisted with data cleaning and formatting to support integration into ML pipelines, and worked with project leads to improve labeling guidelines.

Image Annotation Specialist at Remotask

January 1, 2020 - January 1, 2023

Performed image annotation for computer vision tasks including object detection, semantic segmentation, and keypoint labeling across datasets totaling about 1350 images. Ensured annotation accuracy through multiple rounds of quality assurance and cross-check reviews. Collaborated with ML engineers to align labeling guidelines with project goals and improve overall dataset quality. Trained new team members on annotation tools and labeling best practices, supporting consistent output across the team.