Joseph Kiptanui

Detail-oriented Data Annotation and QA Specialist with over four years of experience supporting AI projects across autonomous driving, geospatial, and agricultural domains. Experienced in reviewing, tagging, and labeling diverse types of data while following detailed guidelines and quality standards. Known for strong attention to detail, clear written communication, and the ability to maintain accuracy and consistency when working with complex or sensitive content.

Reliable, adaptable, and comfortable in fast-paced remote review environments.

Freelance Data Annotator and QA Reviewer at CloudFactory (2024-07 – Present)

Performed pixel-level instance and semantic segmentation using CVAT, Labelbox, and SuperAnnotate, consistently achieving 98%+ QA pass rates. Conducted quality audits and peer reviews, reducing rework by 20% and improving annotation consistency across teams. Reviewed complex and sensitive data in line with detailed project guidelines and quality benchmarks.

Updated class definitions and internal documentation to improve onboarding efficiency and reduce reviewer errors. Maintained high on-time delivery through clear communication and adherence to SLAs.

• Performed pixel-level instance and semantic segmentation using CVAT, Labelbox, and SuperAnnotate, consistently achieving 98%+ QA pass rates
• Conducted quality audits and peer reviews, reducing rework by 20% and improving annotation consistency across teams
• Reviewed complex and sensitive data in line with detailed project guidelines and quality benchmarks
• Updated class definitions and internal documentation to improve onboarding efficiency and reduce reviewer errors
• Maintained high on-time delivery through clear communication and adherence to SLAs

Data Annotator at RYU Data Projects (2024-01 – 2024-06)

Annotated satellite and aerial imagery following strict project specifications and review guidelines. Created accurate polygon and segmentation labels to support model training and analysis. Participated in regular feedback sessions to improve quality, consistency, and guideline understanding.

• Annotated satellite and aerial imagery following strict project specifications and review guidelines
• Created accurate polygon and segmentation labels to support model training and analysis
• Participated in regular feedback sessions to improve quality, consistency, and guideline understanding

Data Annotator at Sama (2021-01 – 2023-12)

Delivered high-quality image and LiDAR annotations for large-scale autonomous vehicle projects. Reviewed labeled data for accuracy and compliance with evolving guidelines. Consistently exceeded quality benchmarks while meeting tight production timelines.

• Delivered high-quality image and LiDAR annotations for large-scale autonomous vehicle projects
• Reviewed labeled data for accuracy and compliance with evolving guidelines
• Consistently exceeded quality benchmarks while meeting tight production timelines

Bachelor of Education (B.Ed) in Arts – Machakos University (2017-01 – 2021-12)

Professional Foundation Program in Python Programming, Computer Science Fundamentals – ALX Africa (2024-01 – 2027-06)