John M.

Key Skills

Software

Labelbox

CVAT

Other

Top Subject Matter

Computer vision dataset annotation (automotive/health/e-commerce)

Video tracking and temporal alignment for autonomous systems

NLP annotation for sentiment/context parsing and intent recognition

Top Data Types

Image

Video

Text

Audio

Document

Top Task Types

Segmentation

Tracking

Entity (NER) Classification

Transcription

Freelancer Overview

Data Labeling & Quality Assurance Specialist (Freelance / Remote). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Labelbox, CVAT, and Prodiigv. Education includes Bachelor of Science, Dedan Kimathi University of Technology (2022) and Kenya Certificate of High School Education, Weru Secondary School (2021). AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Segmentation, Tracking, and Entity (NER) Classification.

Labeling Experience

Data Labeling & Quality Assurance Specialist (Freelance / Remote) - Audio Annotation

OtherAudioTranscription

Processed over 150 hours of multi-speaker audio recordings alongside sequential video annotation efforts. Produced exact semantic timestamps to support time-aligned training data generation for production ML systems. Maintained alignment with client specification and validated outputs using quality assurance frameworks and audit logging. • Generated transcription-aligned time markers for training datasets • Ensured temporal precision for downstream semantic parsing tasks • Performed blind verification and error diagnostics for batch outputs • Documented edge cases and updated criteria iteratively based on audit findings

2025 - Present

Data Labeling & Quality Assurance Specialist (Freelance / Remote) - NLP Projects

TextEntity (NER) Classification

Annotated 2,500+ text samples for structural token parsing, intent matching, and sentiment classification for NLP model training. Delivered labeled outputs aligned to client requirements, maintaining strict accuracy thresholds and evaluation-ready formatting. Applied quality assurance processes including systematic cross-validation tests, blind testing, and audit log maintenance. • Labeled entities and classification-relevant spans for intent and sentiment tasks • Standardized dataset outputs in structured formats such as JSON and CSV • Reviewed and resolved mismatches using root-cause analysis and iterative criteria updates • Supported multilingual pipeline localization across 8+ linguistic sets

2025 - Present

Data Labeling & Quality Assurance Specialist (Freelance / Remote) - Video/Tracking Projects

CVATVideoTracking

Processed over 150 hours of sequential video recordings with multi-speaker audio to produce exact semantic timestamps and pixel-level tracking boundaries. Annotated trajectories, moving objects, and structural boundaries under varying environmental variables for autonomous-vehicle-related use cases. Ensured consistent annotation logic via systematic translation/formatting standardization and audit-ready documentation. • Produced trajectory vector mappings for 2,000+ complex frames • Captured dynamic pedestrian and structural traffic sign boundaries under diverse conditions • Delivered temporally precise outputs for training pipelines • Supported cross-validation and root-cause analysis when mismatched annotations were detected

2025 - Present

Data Labeling & Quality Assurance Specialist (Freelance / Remote)

LabelboxImageSegmentation

Annotated and validated 5,000+ high-resolution images for computer vision training pipelines in automotive, health, and e-commerce contexts. Maintained a 98%+ quality score on validation audits by aligning outputs with granular, multi-page client specifications. Followed rigorous dataset version control and privacy governance to support production-grade ML model training. • Supported bounding boxes, polygons, semantic segmentation, and keypoint tagging in image datasets • Implemented automated batch formatting and dataset standardization workflows (JSON, XML, CSV, COCO) • Conducted inter-annotator agreement style quality checks and blind verification to confirm alignment • Documented edge cases and feedback loops to reduce workflow error rates across successive batches

2025 - Present

Education

Work History