Josephat N.

Key Skills

Software

Sama

Remotasks

CVAT

CloudFactory

Top Subject Matter

Computer Vision datasets for AI/ML training (image/polygon/object tracking)

Computer Vision annotation for AI/ML model development (image, segmentation/polygons, tracking)

Top Data Types

Image

Medical Dicom

Geospatial Tiled Imagery

Top Task Types

Polygon

Tracking

Bounding Box

Segmentation

Polyline

Object Detection

Computer Programming/Coding

Evaluation/Rating

Classification

Entity (NER) Classification

Freelancer Overview

Project Manager / Annotation Quality Control Supervisor at JNEP Services (Feb 2022 – Nov 2024). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, N/A (2022). AI-training focus includes data types such as Image and labeling workflows including Polygon and Tracking.

Labeling Experience

Data Labeling Team Lead at Infralytics (Sep 2023 – Apr 2024)

ImageTracking

Led a data labeling team producing annotated datasets used to train production-grade AI and machine learning models. Performed hands-on image, polygon, bounding box, and object-tracking annotations while setting best-practice standards for the team. Improved labeling efficiency and accuracy by designing and managing optimized workflow processes. • Directed team activities including mentoring junior annotators and reducing rework. • Performed direct annotation work across images, polygons, bounding boxes, and tracking tasks. • Aligned annotation priorities with AI project milestones for on-time dataset delivery. • Implemented workflow improvements to increase throughput without compromising data integrity.

2023 - 2024

Project Manager / Annotation Quality Control Supervisor at JNEP Services (Feb 2022 – Nov 2024)

ImagePolygon

Served as an Annotation Quality Control Supervisor and Project Manager, overseeing end-to-end annotation quality for production AI datasets. Ensured consistent application of labeling guidelines and delivered datasets with a maintained 98% accuracy rate through rigorous multi-tier review and inter-annotator agreement checks. Authored labeling guidelines and SOPs that standardized annotation practices across the team. • Supervised annotators and enforced guideline compliance to reduce labeling errors. • Implemented multi-tier QC cycles and agreement-based validation to improve reliability. • Conducted error analysis and provided feedback to drive continuous quality improvement. • Coordinated task allocation and client requirements to meet SLA-aligned project deadlines.

2022 - 2024

Education

Work History