Jahmii Kipawa

Key Skills

Software

Labelbox

Scale AI

Top Subject Matter

Autonomous vehicles

chatbot AI

computer vision

Top Data Types

Image

Text

Document

Top Task Types

Object Detection

Bounding Box

Segmentation

Freelancer Overview

Senior Data Labeling Specialist. Brings 7+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Labelbox and Scale AI. Education includes Bachelor of Science, University of California, Berkeley (2019). AI-training focus includes data types such as Image and labeling workflows including Object Detection, Bounding Box, and Segmentation.

Labeling Experience

Senior Data Labeling Specialist

LabelboxImageObject Detection

As Senior Data Labeling Specialist, I led a team of 15 annotators labeling computer vision and NLP datasets for autonomous vehicle and chatbot AI projects. I ensured annotation standards and quality assurance with an average quality score of 98.7% over 200,000+ annotations. I coordinated with ML engineers to optimize schema, address edge cases, and audit data labeling outputs. • Managed complex labeling including 3D bounding boxes, polyline annotation, multi-label classification, and entity relationship tagging • Developed annotation guidelines reducing inter-annotator disagreement by 40% • Conducted regular audits and mentored junior labelers, improving team accuracy from 92% to 97%. • Specialized in advanced annotation such as semantic segmentation and text classification.

As Senior Data Labeling Specialist, I led a team of 15 annotators labeling computer vision and NLP datasets for autonomous vehicle and chatbot AI projects. I ensured annotation standards and quality assurance with an average quality score of 98.7% over 200,000+ annotations. I coordinated with ML engineers to optimize schema, address edge cases, and audit data labeling outputs. • Managed complex labeling including 3D bounding boxes, polyline annotation, multi-label classification, and entity relationship tagging • Developed annotation guidelines reducing inter-annotator disagreement by 40% • Conducted regular audits and mentored junior labelers, improving team accuracy from 92% to 97%. • Specialized in advanced annotation such as semantic segmentation and text classification.

2022 - Present

Data Annotation Specialist

Scale AIImageBounding Box

As Data Annotation Specialist, I annotated over 75,000 images for computer vision projects including autonomous driving and medical imaging. I performed bounding box, polygon, keypoint, and classification labels on diverse datasets while participating in RLHF projects. Maintained top 5% quality ranking and documented edge cases to improve guidelines. • Processed multi-language text datasets for sentiment analysis and NER tasks • Supported RLHF by evaluating and ranking AI model outputs • Achieved 99.1% accuracy over 14 months on quality audits • Identified over 150 labeling inconsistencies for guideline improvement.

As Data Annotation Specialist, I annotated over 75,000 images for computer vision projects including autonomous driving and medical imaging. I performed bounding box, polygon, keypoint, and classification labels on diverse datasets while participating in RLHF projects. Maintained top 5% quality ranking and documented edge cases to improve guidelines. • Processed multi-language text datasets for sentiment analysis and NER tasks • Supported RLHF by evaluating and ranking AI model outputs • Achieved 99.1% accuracy over 14 months on quality audits • Identified over 150 labeling inconsistencies for guideline improvement.

2021 - 2022

Data Labeling Associate

Scale AIImageSegmentation

As a Data Labeling Associate, I labeled over 50,000 data points across images, text, audio, and video datasets for ML projects. My work included specialized annotation such as medical image labeling, LiDAR point cloud, audio transcription, and quality auditing. I contributed to team productivity improvements and developed metrics dashboards. • Achieved 97.5% quality accuracy while delivering 800-1,000 daily annotations • Completed training in advanced medical, LiDAR, and audio annotation • Developed dashboards and contributed to UI annotation tool enhancements • Provided feedback that reduced annotation time by 15%.

As a Data Labeling Associate, I labeled over 50,000 data points across images, text, audio, and video datasets for ML projects. My work included specialized annotation such as medical image labeling, LiDAR point cloud, audio transcription, and quality auditing. I contributed to team productivity improvements and developed metrics dashboards. • Achieved 97.5% quality accuracy while delivering 800-1,000 daily annotations • Completed training in advanced medical, LiDAR, and audio annotation • Developed dashboards and contributed to UI annotation tool enhancements • Provided feedback that reduced annotation time by 15%.

2020 - 2021

Education

Work History