Edwin M.

Key Skills

Software

No software listed

Top Subject Matter

AI annotation QA for images

Video Domain Expertise

and LLM outputs

Top Data Types

Image

Video

Text

3D Sensor

Document

Audio

Top Task Types

Transcription

Entity (NER) Classification

Tracking

Freelancer Overview

CloudFactory — AI Data Operations & QA Specialist (Hybrid). Brings 10+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Science, The Cooperative University of Kenya (2020). AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Evaluation, Rating, and Transcription.

Labeling Experience

AI Data Operations & QA Specialist - CloudFactory

ImageTracking

Led QA reviews of AI outputs to ensure compliance with SOPs and training requirements across image, video, and LLM results. Analyzed inconsistencies, errors, and ambiguities in labeled datasets and escalated issues for correction or clarification. Produced structured QA reports identifying recurring issues and workflow gaps to improve overall data quality and alignment. • Conducted quality assurance audits of multi-format AI-generated annotations • Detected anomalies affecting model training quality and object tracking • Synthesized QA findings into documented reports for process improvement • Coordinated with distributed reviewers using Slack, Zoom, and internal platforms

2025 - Present

CloudFactory — AI Data Operations & QA Specialist (Hybrid)

Image

Conducted QA reviews of AI-generated annotations across image, video, and LLM outputs to ensure SOP and training compliance. Identified inconsistencies, errors, ambiguities, and anomalies that could degrade model training quality and escalated items for correction. Synthesized recurring QA findings into structured reports to support workflow improvements and onboarding of reviewers. • Reviewed multi-frame video sequences for consistent object tracking and annotation accuracy. • Performed anomaly detection for mislabeling, visual defects, and contextual mismatches. • Collaborated with distributed teams via Slack/Zoom and internal annotation platforms for alignment. • Authored or contributed to onboarding materials and QA guidelines for consistency across review teams.

2025 - Present

LiDAR & 3D Data Quality Analyst (Contract) - Avala

3D SensorTrackingTranscription

Validated 3D LiDAR datasets for accuracy, alignment, and consistency with project specifications. Monitored object continuity across frames while maintaining annotation integrity and identity consistency. Verified synchronization between LiDAR point clouds and camera feeds and identified spatial misalignments that could affect reliability and training performance. • Performed dataset validation against structured QA frameworks • Checked continuity and identity consistency across multi-frame data • Verified multi-modal synchronization between sensors and feeds • Identified misalignment issues impacting downstream use and model performance

2024 - 2025

Avala — LiDAR & 3D Data Quality Analyst (Contract)

3D Sensor

Reviewed and validated 3D LiDAR datasets to ensure spatial accuracy, alignment, and consistency with project specifications. Tracked object continuity across frames while maintaining identity consistency and annotation integrity. Verified synchronization between LiDAR point clouds and camera feeds to support multi-modal dataset reliability. • Detected spatial misalignments and inconsistencies impacting dataset reliability and downstream training performance. • Followed strict QA frameworks and structured labeling/validation guidelines. • Ensured temporal continuity of objects across frames for coherent 3D annotations. • Assessed multi-modal alignment between sensor data sources.

2024 - 2025

Transcription QA & Review Assistant - Echolabs

AudioTranscription

Performed transcription QA by reviewing audio-to-text outputs for accuracy and formatting consistency. Identified transcription errors, missing context, and inconsistencies and documented issues for correction. Ensured adherence to structured QA guidelines while completing repetitive, high-volume review tasks with reliable attention to detail. • Conducted QA checks on transcribed audio and text deliverables • Logged transcription errors and quality issues in review documentation • Verified formatting and context consistency across outputs • Followed standardized QA guidelines for high-volume work

2024 - 2024

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Education

Work History